Overview

Dataset statistics

Number of variables31
Number of observations500
Missing cells566
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory128.1 KiB
Average record size in memory262.3 B

Variable types

Text2
Categorical21
Numeric7
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 필수보충정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092814/fileData.do

Alerts

국가계정코드값 has constant value ""Constant
국가결산단계구분코드 has constant value ""Constant
명세서대분류코드 has constant value ""Constant
삭제여부 has constant value ""Constant
최종수정수 has constant value ""Constant
명세서중분류코드 is highly imbalanced (81.6%)Imbalance
제2항목값 has 15 (3.0%) missing valuesMissing
제3항목값 has 14 (2.8%) missing valuesMissing
제4항목값 has 15 (3.0%) missing valuesMissing
제5항목값 has 15 (3.0%) missing valuesMissing
제6항목값 has 15 (3.0%) missing valuesMissing
제7항목값 has 246 (49.2%) missing valuesMissing
제8항목값 has 246 (49.2%) missing valuesMissing
필수보충정보ID has unique valuesUnique
제2항목값 has 184 (36.8%) zerosZeros
제3항목값 has 220 (44.0%) zerosZeros
제5항목값 has 197 (39.4%) zerosZeros
제6항목값 has 437 (87.4%) zerosZeros
제7항목값 has 50 (10.0%) zerosZeros
제8항목값 has 218 (43.6%) zerosZeros

Reproduction

Analysis started2023-12-12 06:40:13.038167
Analysis finished2023-12-12 06:40:13.487172
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

필수보충정보ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T15:40:13.682101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

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

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row9dnSMVfs5S
2nd row9dnSMVfqt4
3rd row9dnSMVfqcN
4th row9dnSMVfhsH
5th row9dnSMVfhkm
ValueCountFrequency (%)
9dnsmvfs5s 1
 
0.2%
9dnoghtqhg 1
 
0.2%
9dnoghtkue 1
 
0.2%
9dnoghtk2u 1
 
0.2%
9dnoghtlbq 1
 
0.2%
9dnoghtlkv 1
 
0.2%
9dnoghtlrg 1
 
0.2%
9dnoghtlev 1
 
0.2%
9dnoghtlmh 1
 
0.2%
9dnoghtl19 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T15:40:14.045240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 554
 
11.1%
9 519
 
10.4%
n 424
 
8.5%
o 236
 
4.7%
T 163
 
3.3%
r 153
 
3.1%
H 147
 
2.9%
S 143
 
2.9%
m 137
 
2.7%
a 133
 
2.7%
Other values (52) 2391
47.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2666
53.3%
Uppercase Letter 1486
29.7%
Decimal Number 848
 
17.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 554
20.8%
n 424
15.9%
o 236
8.9%
r 153
 
5.7%
m 137
 
5.1%
a 133
 
5.0%
g 131
 
4.9%
y 123
 
4.6%
v 114
 
4.3%
u 95
 
3.6%
Other values (16) 566
21.2%
Uppercase Letter
ValueCountFrequency (%)
T 163
11.0%
H 147
 
9.9%
S 143
 
9.6%
M 130
 
8.7%
U 127
 
8.5%
Y 98
 
6.6%
E 88
 
5.9%
J 69
 
4.6%
I 64
 
4.3%
K 55
 
3.7%
Other values (16) 402
27.1%
Decimal Number
ValueCountFrequency (%)
9 519
61.2%
0 121
 
14.3%
7 39
 
4.6%
2 32
 
3.8%
1 29
 
3.4%
6 27
 
3.2%
8 24
 
2.8%
5 22
 
2.6%
4 21
 
2.5%
3 14
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 4152
83.0%
Common 848
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 554
 
13.3%
n 424
 
10.2%
o 236
 
5.7%
T 163
 
3.9%
r 153
 
3.7%
H 147
 
3.5%
S 143
 
3.4%
m 137
 
3.3%
a 133
 
3.2%
g 131
 
3.2%
Other values (42) 1931
46.5%
Common
ValueCountFrequency (%)
9 519
61.2%
0 121
 
14.3%
7 39
 
4.6%
2 32
 
3.8%
1 29
 
3.4%
6 27
 
3.2%
8 24
 
2.8%
5 22
 
2.6%
4 21
 
2.5%
3 14
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 554
 
11.1%
9 519
 
10.4%
n 424
 
8.5%
o 236
 
4.7%
T 163
 
3.3%
r 153
 
3.1%
H 147
 
2.9%
S 143
 
2.9%
m 137
 
2.7%
a 133
 
2.7%
Other values (52) 2391
47.8%

회계년월
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
202108
181 
202109
180 
202107
139 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202109
2nd row202109
3rd row202109
4th row202109
5th row202109

Common Values

ValueCountFrequency (%)
202108 181
36.2%
202109 180
36.0%
202107 139
27.8%

Length

2023-12-12T15:40:14.221914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:14.412434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202108 181
36.2%
202109 180
36.0%
202107 139
27.8%

소관코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
79
323 
69
177 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row79
2nd row79
3rd row79
4th row79
5th row79

Common Values

ValueCountFrequency (%)
79 323
64.6%
69 177
35.4%

Length

2023-12-12T15:40:14.654618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:14.753357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
79 323
64.6%
69 177
35.4%

국가결산회계구분코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
574
323 
578
177 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
574 323
64.6%
578 177
35.4%

Length

2023-12-12T15:40:14.873991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:14.957290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
574 323
64.6%
578 177
35.4%

국가계정코드값
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

2023-12-12T15:40:15.053522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:15.146497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

국가결산단계구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
21
500 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
21 500
100.0%

Length

2023-12-12T15:40:15.262578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:15.345968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
21 500
100.0%

명세서대분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
F3
500 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF3
2nd rowF3
3rd rowF3
4th rowF3
5th rowF3

Common Values

ValueCountFrequency (%)
F3 500
100.0%

Length

2023-12-12T15:40:15.458439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:15.558311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f3 500
100.0%

명세서중분류코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
F3030
486 
70
 
14

Length

Max length5
Median length5
Mean length4.916
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF3030
2nd rowF3030
3rd rowF3030
4th rowF3030
5th rowF3030

Common Values

ValueCountFrequency (%)
F3030 486
97.2%
70 14
 
2.8%

Length

2023-12-12T15:40:15.689511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:15.802455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f3030 486
97.2%
70 14
 
2.8%

명세서일련번호
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
50
254 
70
217 
80
29 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70
2nd row70
3rd row70
4th row70
5th row70

Common Values

ValueCountFrequency (%)
50 254
50.8%
70 217
43.4%
80 29
 
5.8%

Length

2023-12-12T15:40:15.926440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:16.031393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50 254
50.8%
70 217
43.4%
80 29
 
5.8%

필수보충정보일련번호
Real number (ℝ)

Distinct95
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.788
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T15:40:16.180234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q112
median25.5
Q343.25
95-th percentile83
Maximum95
Range94
Interquartile range (IQR)31.25

Descriptive statistics

Standard deviation24.523414
Coefficient of variation (CV)0.79652509
Kurtosis-0.053549679
Mean30.788
Median Absolute Deviation (MAD)15
Skewness0.88946986
Sum15394
Variance601.39785
MonotonicityNot monotonic
2023-12-12T15:40:16.346239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 28
 
5.6%
2 14
 
2.8%
3 14
 
2.8%
37 9
 
1.8%
10 9
 
1.8%
27 9
 
1.8%
30 9
 
1.8%
32 9
 
1.8%
26 9
 
1.8%
4 9
 
1.8%
Other values (85) 381
76.2%
ValueCountFrequency (%)
1 28
5.6%
2 14
2.8%
3 14
2.8%
4 9
 
1.8%
5 9
 
1.8%
6 8
 
1.6%
7 8
 
1.6%
8 8
 
1.6%
9 9
 
1.8%
10 9
 
1.8%
ValueCountFrequency (%)
95 2
0.4%
94 2
0.4%
93 2
0.4%
92 2
0.4%
91 2
0.4%
90 2
0.4%
89 2
0.4%
88 2
0.4%
87 2
0.4%
86 2
0.4%

제2항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct103
Distinct (%)21.2%
Missing15
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1.0289467 × 1010
Minimum-1.17 × 1012
Maximum1.78 × 1012
Zeros184
Zeros (%)36.8%
Negative48
Negative (%)9.6%
Memory size4.5 KiB
2023-12-12T15:40:16.481324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.17 × 1012
5-th percentile-1.4 × 1010
Q10
median41040000
Q351140000
95-th percentile5.854267 × 109
Maximum1.78 × 1012
Range2.95 × 1012
Interquartile range (IQR)51140000

Descriptive statistics

Standard deviation1.8135396 × 1011
Coefficient of variation (CV)17.625205
Kurtosis53.207302
Mean1.0289467 × 1010
Median Absolute Deviation (MAD)41040000
Skewness5.2511297
Sum4.9903914 × 1012
Variance3.2889259 × 1022
MonotonicityNot monotonic
2023-12-12T15:40:16.735797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 184
36.8%
51070000 13
 
2.6%
51310000 10
 
2.0%
51300000 8
 
1.6%
41040000 8
 
1.6%
41060000 8
 
1.6%
41070000 8
 
1.6%
51330000 8
 
1.6%
51250000 8
 
1.6%
51200000 8
 
1.6%
Other values (93) 222
44.4%
(Missing) 15
 
3.0%
ValueCountFrequency (%)
-1170000000000 1
 
0.2%
-783000000000 1
 
0.2%
-370000000000 6
1.2%
-344000000000 1
 
0.2%
-185000000000 1
 
0.2%
-179000000000 1
 
0.2%
-157000000000 1
 
0.2%
-154000000000 1
 
0.2%
-93748184078 1
 
0.2%
-83299191449 1
 
0.2%
ValueCountFrequency (%)
1780000000000 1
0.2%
1690000000000 1
0.2%
1540000000000 1
0.2%
993000000000 1
0.2%
956000000000 1
0.2%
899000000000 1
0.2%
869000000000 1
0.2%
723000000000 1
0.2%
669000000000 1
0.2%
119000000000 1
0.2%

제3항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.9%
Missing14
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean1.0067182 × 1010
Minimum0
Maximum1.15 × 1012
Zeros220
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T15:40:16.912273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile2
Maximum1.15 × 1012
Range1.15 × 1012
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.8160686 × 1010
Coefficient of variation (CV)9.7505622
Kurtosis114.50384
Mean1.0067182 × 1010
Median Absolute Deviation (MAD)1
Skewness10.656012
Sum4.8926505 × 1012
Variance9.6355203 × 1021
MonotonicityNot monotonic
2023-12-12T15:40:17.050902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 220
44.0%
2 216
43.2%
1 38
 
7.6%
239000000000 2
 
0.4%
24609717899 2
 
0.4%
1150000000000 2
 
0.4%
990000000000 2
 
0.4%
22434295022 2
 
0.4%
20281252279 2
 
0.4%
(Missing) 14
 
2.8%
ValueCountFrequency (%)
0 220
44.0%
1 38
 
7.6%
2 216
43.2%
20281252279 2
 
0.4%
22434295022 2
 
0.4%
24609717899 2
 
0.4%
239000000000 2
 
0.4%
990000000000 2
 
0.4%
1150000000000 2
 
0.4%
ValueCountFrequency (%)
1150000000000 2
 
0.4%
990000000000 2
 
0.4%
239000000000 2
 
0.4%
24609717899 2
 
0.4%
22434295022 2
 
0.4%
20281252279 2
 
0.4%
2 216
43.2%
1 38
 
7.6%
0 220
44.0%

제4항목값
Text

MISSING 

Distinct97
Distinct (%)20.0%
Missing15
Missing (%)3.0%
Memory size4.0 KiB
2023-12-12T15:40:17.337782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8
Mean length7.8721649
Min length5

Characters and Unicode

Total characters3818
Distinct characters112
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
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 row30000000
2nd row20000000
3rd row10000000
4th row26000000
5th row23000000
ValueCountFrequency (%)
10000000 20
 
3.9%
2.복리후생비 8
 
1.5%
3.소모품비 8
 
1.5%
4.인쇄비 8
 
1.5%
5.광고선전비 8
 
1.5%
6.지급수수료 8
 
1.5%
7.세금과공과 8
 
1.5%
1.인건비 8
 
1.5%
21100000 6
 
1.2%
4.기타수익 6
 
1.2%
Other values (94) 430
83.0%
2023-12-12T15:40:17.751324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1188
31.1%
2 380
 
10.0%
1 294
 
7.7%
. 254
 
6.7%
비 163
 
4.3%
수 83
 
2.2%
3 63
 
1.7%
익 53
 
1.4%
4 42
 
1.1%
6 40
 
1.0%
Other values (102) 1258
32.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2146
56.2%
Other Letter 1267
33.2%
Other Punctuation 254
 
6.7%
Letter Number 73
 
1.9%
Space Separator 33
 
0.9%
Dash Punctuation 15
 
0.4%
Math Symbol 10
 
0.3%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 163
 
12.9%
수 83
 
6.6%
익 53
 
4.2%
용 37
 
2.9%
지 33
 
2.6%
자 27
 
2.1%
이 27
 
2.1%
료 27
 
2.1%
급 27
 
2.1%
기 26
 
2.1%
Other values (77) 764
60.3%
Decimal Number
ValueCountFrequency (%)
0 1188
55.4%
2 380
 
17.7%
1 294
 
13.7%
3 63
 
2.9%
4 42
 
2.0%
6 40
 
1.9%
5 40
 
1.9%
8 38
 
1.8%
7 33
 
1.5%
9 28
 
1.3%
Letter Number
ValueCountFrequency (%)
Ⅴ 10
13.7%
Ⅱ 10
13.7%
Ⅶ 10
13.7%
Ⅰ 10
13.7%
Ⅵ 10
13.7%
Ⅳ 10
13.7%
Ⅲ 8
11.0%
Ⅷ 5
6.8%
Dash Punctuation
ValueCountFrequency (%)
－ 10
66.7%
- 5
33.3%
Other Punctuation
ValueCountFrequency (%)
. 254
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Math Symbol
ValueCountFrequency (%)
＋ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2478
64.9%
Hangul 1267
33.2%
Latin 73
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 163
 
12.9%
수 83
 
6.6%
익 53
 
4.2%
용 37
 
2.9%
지 33
 
2.6%
자 27
 
2.1%
이 27
 
2.1%
료 27
 
2.1%
급 27
 
2.1%
기 26
 
2.1%
Other values (77) 764
60.3%
Common
ValueCountFrequency (%)
0 1188
47.9%
2 380
 
15.3%
1 294
 
11.9%
. 254
 
10.3%
3 63
 
2.5%
4 42
 
1.7%
6 40
 
1.6%
5 40
 
1.6%
8 38
 
1.5%
33
 
1.3%
Other values (7) 106
 
4.3%
Latin
ValueCountFrequency (%)
Ⅴ 10
13.7%
Ⅱ 10
13.7%
Ⅶ 10
13.7%
Ⅰ 10
13.7%
Ⅵ 10
13.7%
Ⅳ 10
13.7%
Ⅲ 8
11.0%
Ⅷ 5
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2458
64.4%
Hangul 1267
33.2%
Number Forms 73
 
1.9%
None 20
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1188
48.3%
2 380
 
15.5%
1 294
 
12.0%
. 254
 
10.3%
3 63
 
2.6%
4 42
 
1.7%
6 40
 
1.6%
5 40
 
1.6%
8 38
 
1.5%
33
 
1.3%
Other values (5) 86
 
3.5%
Hangul
ValueCountFrequency (%)
비 163
 
12.9%
수 83
 
6.6%
익 53
 
4.2%
용 37
 
2.9%
지 33
 
2.6%
자 27
 
2.1%
이 27
 
2.1%
료 27
 
2.1%
급 27
 
2.1%
기 26
 
2.1%
Other values (77) 764
60.3%
Number Forms
ValueCountFrequency (%)
Ⅴ 10
13.7%
Ⅱ 10
13.7%
Ⅶ 10
13.7%
Ⅰ 10
13.7%
Ⅵ 10
13.7%
Ⅳ 10
13.7%
Ⅲ 8
11.0%
Ⅷ 5
6.8%
None
ValueCountFrequency (%)
＋ 10
50.0%
－ 10
50.0%

제5항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct264
Distinct (%)54.4%
Missing15
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean2.0941235 × 1010
Minimum-3.17 × 1012
Maximum4.5 × 1012
Zeros197
Zeros (%)39.4%
Negative41
Negative (%)8.2%
Memory size4.5 KiB
2023-12-12T15:40:17.909453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.17 × 1012
5-th percentile-8 × 109
Q10
median1613654
Q31.5822642 × 109
95-th percentile2.278 × 1011
Maximum4.5 × 1012
Range7.67 × 1012
Interquartile range (IQR)1.5822642 × 109

Descriptive statistics

Standard deviation5.3216892 × 1011
Coefficient of variation (CV)25.412491
Kurtosis39.10333
Mean2.0941235 × 1010
Median Absolute Deviation (MAD)88050586
Skewness1.1086923
Sum1.0156499 × 1013
Variance2.8320376 × 1023
MonotonicityNot monotonic
2023-12-12T15:40:18.075634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 197
39.4%
-8000000000 5
 
1.0%
-3050000000000 4
 
0.8%
250000000000 3
 
0.6%
97372236 3
 
0.6%
1613654 3
 
0.6%
7838709064 3
 
0.6%
232000000 2
 
0.4%
-1689955 2
 
0.4%
-79221692 2
 
0.4%
Other values (254) 261
52.2%
(Missing) 15
 
3.0%
ValueCountFrequency (%)
-3170000000000 2
0.4%
-3050000000000 4
0.8%
-1450000000000 1
 
0.2%
-856000000000 1
 
0.2%
-494000000000 1
 
0.2%
-328000000000 1
 
0.2%
-271000000000 1
 
0.2%
-119000000000 1
 
0.2%
-73825243970 1
 
0.2%
-69797876177 1
 
0.2%
ValueCountFrequency (%)
4500000000000 1
0.2%
4180000000000 1
0.2%
4060000000000 1
0.2%
2560000000000 1
0.2%
2170000000000 1
0.2%
1890000000000 1
0.2%
879000000000 1
0.2%
868000000000 1
0.2%
834000000000 1
0.2%
783000000000 1
0.2%

제6항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct40
Distinct (%)8.2%
Missing15
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1.5519367 × 1010
Minimum-1.15 × 1012
Maximum1.32 × 1012
Zeros437
Zeros (%)87.4%
Negative11
Negative (%)2.2%
Memory size4.5 KiB
2023-12-12T15:40:18.222763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.15 × 1012
5-th percentile0
Q10
median0
Q30
95-th percentile2.1892081 × 1010
Maximum1.32 × 1012
Range2.47 × 1012
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5510629 × 1011
Coefficient of variation (CV)9.9943695
Kurtosis38.285529
Mean1.5519367 × 1010
Median Absolute Deviation (MAD)0
Skewness3.1220754
Sum7.5268932 × 1012
Variance2.4057962 × 1022
MonotonicityNot monotonic
2023-12-12T15:40:18.387320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 437
87.4%
26825747294 2
 
0.4%
21892080731 2
 
0.4%
-22409884064 2
 
0.4%
23920544096 2
 
0.4%
958000000000 2
 
0.4%
1090000000000 2
 
0.4%
450518464 2
 
0.4%
-24585306941 2
 
0.4%
-122000000000 2
 
0.4%
Other values (30) 30
 
6.0%
(Missing) 15
 
3.0%
ValueCountFrequency (%)
-1150000000000 1
 
0.2%
-990000000000 1
 
0.2%
-391000000000 1
 
0.2%
-342000000000 1
 
0.2%
-238000000000 1
 
0.2%
-122000000000 2
 
0.4%
-24585306941 2
 
0.4%
-22409884064 2
 
0.4%
0 437
87.4%
450518464 2
 
0.4%
ValueCountFrequency (%)
1320000000000 1
0.2%
1090000000000 2
0.4%
958000000000 2
0.4%
842000000000 1
0.2%
755000000000 1
0.2%
699000000000 1
0.2%
648000000000 1
0.2%
604000000000 1
0.2%
527000000000 1
0.2%
459000000000 1
0.2%

제7항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct192
Distinct (%)75.6%
Missing246
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean2.3801778 × 1010
Minimum-79221692
Maximum8.56 × 1011
Zeros50
Zeros (%)10.0%
Negative2
Negative (%)0.4%
Memory size4.5 KiB
2023-12-12T15:40:18.539557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-79221692
5-th percentile0
Q19564769.2
median4.7619252 × 108
Q33.1305264 × 109
95-th percentile7.3403793 × 1010
Maximum8.56 × 1011
Range8.5607922 × 1011
Interquartile range (IQR)3.1209617 × 109

Descriptive statistics

Standard deviation1.0559907 × 1011
Coefficient of variation (CV)4.4366044
Kurtosis34.744618
Mean2.3801778 × 1010
Median Absolute Deviation (MAD)4.7619252 × 108
Skewness5.7831019
Sum6.0456517 × 1012
Variance1.1151164 × 1022
MonotonicityNot monotonic
2023-12-12T15:40:18.683871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 50
 
10.0%
177300000 3
 
0.6%
287183431 3
 
0.6%
1210492 3
 
0.6%
119000000000 2
 
0.4%
-79221692 2
 
0.4%
1368400 2
 
0.4%
8190200 2
 
0.4%
253000000 2
 
0.4%
15206400 2
 
0.4%
Other values (182) 183
36.6%
(Missing) 246
49.2%
ValueCountFrequency (%)
-79221692 2
 
0.4%
0 50
10.0%
1210492 3
 
0.6%
1368400 2
 
0.4%
1464554 1
 
0.2%
1521554 1
 
0.2%
2759400 1
 
0.2%
3097200 1
 
0.2%
3155879 1
 
0.2%
8190200 2
 
0.4%
ValueCountFrequency (%)
856000000000 1
0.2%
711000000000 1
0.2%
697000000000 1
0.2%
626000000000 1
0.2%
494000000000 1
0.2%
466000000000 1
0.2%
408000000000 1
0.2%
353000000000 1
0.2%
134000000000 1
0.2%
133000000000 1
0.2%

제8항목값
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)13.4%
Missing246
Missing (%)49.2%
Infinite0
Infinite (%)0.0%
Mean1.6901316 × 1010
Minimum-1.09 × 1012
Maximum1.54 × 1012
Zeros218
Zeros (%)43.6%
Negative8
Negative (%)1.6%
Memory size4.5 KiB
2023-12-12T15:40:18.841220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.09 × 1012
5-th percentile0
Q10
median0
Q30
95-th percentile9.099822 × 1010
Maximum1.54 × 1012
Range2.63 × 1012
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7760946 × 1011
Coefficient of variation (CV)10.508617
Kurtosis35.759302
Mean1.6901316 × 1010
Median Absolute Deviation (MAD)0
Skewness2.4301491
Sum4.2929342 × 1012
Variance3.154512 × 1022
MonotonicityNot monotonic
2023-12-12T15:40:19.005267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 218
43.6%
-23920544096 2
 
0.4%
320729454 2
 
0.4%
-26825747294 2
 
0.4%
13271657282 1
 
0.2%
26801871509 1
 
0.2%
421000000000 1
 
0.2%
161000000000 1
 
0.2%
181000000000 1
 
0.2%
6582896748 1
 
0.2%
Other values (24) 24
 
4.8%
(Missing) 246
49.2%
ValueCountFrequency (%)
-1090000000000 1
 
0.2%
-958000000000 1
 
0.2%
-357000000000 1
 
0.2%
-315000000000 1
 
0.2%
-26825747294 2
 
0.4%
-23920544096 2
 
0.4%
0 218
43.6%
320729454 2
 
0.4%
1495707572 1
 
0.2%
1710279741 1
 
0.2%
ValueCountFrequency (%)
1540000000000 1
0.2%
940000000000 1
0.2%
817000000000 1
0.2%
731000000000 1
0.2%
643000000000 1
0.2%
575000000000 1
0.2%
479000000000 1
0.2%
421000000000 1
0.2%
181000000000 1
0.2%
161000000000 1
0.2%

제9항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:19.165248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:19.291835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제10항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:19.405177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:19.523135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제11항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:19.641963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:19.744755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제12항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:19.871128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:19.980259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제13항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:20.110865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:20.225148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제14항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:20.360805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:20.476838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제15항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:20.884626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:20.985240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제16항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:21.089331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:21.183228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제17항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:21.296396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:21.412851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제18항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:21.517857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:21.624470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제19항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:21.747775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:21.924144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

제20항목값
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
254 
<NA>
246 

Length

Max length4
Median length1
Mean length2.476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
254
50.8%
<NA> 246
49.2%

Length

2023-12-12T15:40:22.087797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:22.241184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 246
100.0%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-12T15:40:22.349760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-12T15:40:22.470699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:40:22.572485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

Sample

필수보충정보ID회계년월소관코드국가결산회계구분코드국가계정코드값국가결산단계구분코드명세서대분류코드명세서중분류코드명세서일련번호필수보충정보일련번호제2항목값제3항목값제4항목값제5항목값제6항목값제7항목값제8항목값제9항목값제10항목값제11항목값제12항목값제13항목값제14항목값제15항목값제16항목값제17항목값제18항목값제19항목값제20항목값삭제여부최종수정수
09dnSMVfs5S20210979574021F3F303070370239000000000300000000-122000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
19dnSMVfqt420210979574021F3F30307020239000000000200000000-122000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
29dnSMVfqcN20210979574021F3F3030701001000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
39dnSMVfhsH20210979574021F3F30307033002600000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
49dnSMVfhkm20210979574021F3F30307034-370000000000023000000-31700000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
59dnSMVfhco20210979574021F3F3030703178000000000002100000045000000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
69dnSMVfg0x20210979574021F3F30307015-1170000000000022000000-14500000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
79dnSMUwoKF20210979574021F3F30307031002218000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
89dnSMUwoEQ20210979574021F3F30307020002207000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
99dnSMUwoyf20210979574021F3F30307019002206000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
필수보충정보ID회계년월소관코드국가결산회계구분코드국가계정코드값국가결산단계구분코드명세서대분류코드명세서중분류코드명세서일련번호필수보충정보일련번호제2항목값제3항목값제4항목값제5항목값제6항목값제7항목값제8항목값제9항목값제10항목값제11항목값제12항목값제13항목값제14항목값제15항목값제16항목값제17항목값제18항목값제19항목값제20항목값삭제여부최종수정수
4909dmajJwHHP20210769578021F3F30307016002202000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4919dmajJwHxG20210769578021F3F30307026002213000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4929dmajJwGPb20210769578021F3F30307012002108000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4939dmajJwGH120210769578021F3F30307010002106000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4949dmajJwGwr20210769578021F3F3030705119000000000021010000443000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4959dmajJwGko20210769578021F3F3030709002105000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4969dmajJwF4a20210769578021F3F30307035002308000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4979dmajJwFWZ20210769578021F3F30307013002110000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4989dmajJwFPm20210769578021F3F30307014585850428902111000052447426600<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1
4999dmajJwFIO20210769578021F3F3030704-2681528263021120000-744316340<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N1