Overview

Dataset statistics

Number of variables21
Number of observations3600
Missing cells46482
Missing cells (%)61.5%
Duplicate rows181
Duplicate rows (%)5.0%
Total size in memory597.8 KiB
Average record size in memory170.0 B

Variable types

Text17
Categorical2
Unsupported1
DateTime1

Dataset

Description주택금융공사 신탁자산 현황에 대한 자료로 선순위 증권 발행액, 발행이율, 선순위증권 산황액 등 및 후순위 증권 발행액, 후순위증권 상환액 등의 정보를 제공
Author한국주택금융공사
URLhttps://www.data.go.kr/data/3071506/fileData.do

Alerts

Unnamed: 15 has constant value ""Constant
Unnamed: 16 has constant value ""Constant
Unnamed: 17 has constant value ""Constant
Unnamed: 18 has constant value ""Constant
Unnamed: 19 has constant value ""Constant
Dataset has 181 (5.0%) duplicate rowsDuplicates
트랜치명 is highly imbalanced (59.2%)Imbalance
Unnamed: 20 is highly imbalanced (99.6%)Imbalance
발행금액 has 2261 (62.8%) missing valuesMissing
발행이율 has 2259 (62.7%) missing valuesMissing
발행만기일 has 2263 (62.9%) missing valuesMissing
만기상환일 has 3096 (86.0%) missing valuesMissing
만기상환금액 has 3124 (86.8%) missing valuesMissing
콜옵션행사상환일 has 1192 (33.1%) missing valuesMissing
콜옵션행사상환금액 has 1202 (33.4%) missing valuesMissing
상환합계 has 171 (4.8%) missing valuesMissing
잔액트랜치 has 2338 (64.9%) missing valuesMissing
잔액이율 has 2333 (64.8%) missing valuesMissing
반액만기일 has 2331 (64.8%) missing valuesMissing
원금잔액 has 2317 (64.4%) missing valuesMissing
Unnamed: 14 has 3600 (100.0%) missing valuesMissing
Unnamed: 15 has 3599 (> 99.9%) missing valuesMissing
Unnamed: 16 has 3599 (> 99.9%) missing valuesMissing
Unnamed: 17 has 3599 (> 99.9%) missing valuesMissing
Unnamed: 18 has 3599 (> 99.9%) missing valuesMissing
Unnamed: 19 has 3599 (> 99.9%) missing valuesMissing
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 23:41:16.558221
Analysis finished2023-12-12 23:41:17.215142
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

풀명
Text

Distinct148
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
2023-12-13T08:41:17.464581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.3108333
Min length1

Characters and Unicode

Total characters22719
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.3%

Sample

1st rowJan-00
2nd rowJan-00
3rd rowJan-00
4th rowJan-00
5th rowJan-00
ValueCountFrequency (%)
09-feb 68
 
1.9%
09-mar 67
 
1.9%
09-may 66
 
1.8%
09-jul 63
 
1.7%
2011-20 63
 
1.7%
2009-13 59
 
1.6%
12-dec 54
 
1.5%
10-jun 53
 
1.5%
12-nov 50
 
1.4%
10-aug 49
 
1.4%
Other values (136) 3014
83.6%
2023-12-13T08:41:17.901805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 3593
15.8%
0 3449
15.2%
1 2944
13.0%
2 2687
11.8%
a 847
 
3.7%
J 767
 
3.4%
9 630
 
2.8%
u 599
 
2.6%
e 590
 
2.6%
n 567
 
2.5%
Other values (26) 6046
26.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11790
51.9%
Lowercase Letter 4878
21.5%
Dash Punctuation 3593
 
15.8%
Uppercase Letter 2439
 
10.7%
Other Punctuation 13
 
0.1%
Space Separator 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 847
17.4%
u 599
12.3%
e 590
12.1%
n 567
11.6%
r 510
10.5%
b 391
8.0%
p 315
 
6.5%
y 248
 
5.1%
l 200
 
4.1%
c 198
 
4.1%
Other values (4) 413
8.5%
Decimal Number
ValueCountFrequency (%)
0 3449
29.3%
1 2944
25.0%
2 2687
22.8%
9 630
 
5.3%
3 483
 
4.1%
5 385
 
3.3%
8 336
 
2.8%
4 308
 
2.6%
7 291
 
2.5%
6 277
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
J 767
31.4%
M 532
21.8%
F 391
16.0%
A 373
15.3%
D 110
 
4.5%
N 89
 
3.6%
S 89
 
3.6%
O 88
 
3.6%
Other Punctuation
ValueCountFrequency (%)
" 10
76.9%
. 3
 
23.1%
Dash Punctuation
ValueCountFrequency (%)
- 3593
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15402
67.8%
Latin 7317
32.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 847
11.6%
J 767
10.5%
u 599
 
8.2%
e 590
 
8.1%
n 567
 
7.7%
M 532
 
7.3%
r 510
 
7.0%
b 391
 
5.3%
F 391
 
5.3%
A 373
 
5.1%
Other values (12) 1750
23.9%
Common
ValueCountFrequency (%)
- 3593
23.3%
0 3449
22.4%
1 2944
19.1%
2 2687
17.4%
9 630
 
4.1%
3 483
 
3.1%
5 385
 
2.5%
8 336
 
2.2%
4 308
 
2.0%
7 291
 
1.9%
Other values (4) 296
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 3593
15.8%
0 3449
15.2%
1 2944
13.0%
2 2687
11.8%
a 847
 
3.7%
J 767
 
3.4%
9 630
 
2.8%
u 599
 
2.6%
e 590
 
2.6%
n 567
 
2.5%
Other values (26) 6046
26.6%

트랜치명
Categorical

IMBALANCE 

Distinct46
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
2260 
01-01
 
164
02-01
 
153
01-03
 
146
01-02
 
145
Other values (41)
732 

Length

Max length255
Median length4
Mean length4.5433333
Min length1

Unique

Unique26 ?
Unique (%)0.7%

Sample

1st row01-01
2nd row01-02
3rd row01-03
4th row01-04
5th row01-05

Common Values

ValueCountFrequency (%)
<NA> 2260
62.8%
01-01 164
 
4.6%
02-01 153
 
4.2%
01-03 146
 
4.1%
01-02 145
 
4.0%
01-06 144
 
4.0%
01-04 141
 
3.9%
01-05 133
 
3.7%
01-07 130
 
3.6%
01-08 127
 
3.5%
Other values (36) 57
 
1.6%

Length

2023-12-13T08:41:18.041598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 2260
62.0%
01-01 164
 
4.5%
02-01 153
 
4.2%
01-03 146
 
4.0%
01-02 145
 
4.0%
01-06 144
 
3.9%
01-04 141
 
3.9%
01-05 133
 
3.6%
01-07 130
 
3.6%
01-08 127
 
3.5%
Other values (38) 105
 
2.9%

발행금액
Text

MISSING 

Distinct300
Distinct (%)22.4%
Missing2261
Missing (%)62.8%
Memory size28.3 KiB
2023-12-13T08:41:18.259197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length14
Mean length13.550411
Min length1

Characters and Unicode

Total characters18144
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197 ?
Unique (%)14.7%

Sample

1st row22,000,000,000
2nd row10,000,000,000
3rd row12,000,000,000
4th row27,000,000,000
5th row33,000,000,000
ValueCountFrequency (%)
10,000,000,000 130
 
8.8%
50,000,000,000 102
 
6.9%
80,000,000,000 79
 
5.3%
75
 
5.1%
40,000,000,000 73
 
4.9%
60,000,000,000 71
 
4.8%
30,000,000,000 59
 
4.0%
70,000,000,000 57
 
3.9%
90,000,000,000 54
 
3.7%
110,000,000,000 39
 
2.6%
Other values (286) 739
50.0%
2023-12-13T08:41:18.609940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11867
65.4%
, 3753
 
20.7%
1 567
 
3.1%
5 271
 
1.5%
3 233
 
1.3%
227
 
1.3%
2 206
 
1.1%
4 195
 
1.1%
6 167
 
0.9%
8 158
 
0.9%
Other values (10) 500
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13949
76.9%
Other Punctuation 3927
 
21.6%
Space Separator 227
 
1.3%
Dash Punctuation 35
 
0.2%
Control 3
 
< 0.1%
Other Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11867
85.1%
1 567
 
4.1%
5 271
 
1.9%
3 233
 
1.7%
2 206
 
1.5%
4 195
 
1.4%
6 167
 
1.2%
8 158
 
1.1%
7 157
 
1.1%
9 128
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 3753
95.6%
" 150
 
3.8%
. 12
 
0.3%
% 12
 
0.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Space Separator
ValueCountFrequency (%)
227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Control
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18141
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11867
65.4%
, 3753
 
20.7%
1 567
 
3.1%
5 271
 
1.5%
3 233
 
1.3%
227
 
1.3%
2 206
 
1.1%
4 195
 
1.1%
6 167
 
0.9%
8 158
 
0.9%
Other values (7) 497
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18141
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11867
65.4%
, 3753
 
20.7%
1 567
 
3.1%
5 271
 
1.5%
3 233
 
1.3%
227
 
1.3%
2 206
 
1.1%
4 195
 
1.1%
6 167
 
0.9%
8 158
 
0.9%
Other values (7) 497
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

발행이율
Text

MISSING 

Distinct476
Distinct (%)35.5%
Missing2259
Missing (%)62.7%
Memory size28.3 KiB
2023-12-13T08:41:18.964254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length5
Mean length5.1856823
Min length1

Characters and Unicode

Total characters6954
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)15.0%

Sample

1st row8.15%
2nd row8.57%
3rd row8.81%
4th row9.01%
5th row9.16%
ValueCountFrequency (%)
0 69
 
4.9%
39
 
2.8%
000 25
 
1.8%
변동 18
 
1.3%
3.22 12
 
0.9%
3.80 12
 
0.9%
3.14 11
 
0.8%
3.76 10
 
0.7%
3.02 10
 
0.7%
4.08 9
 
0.6%
Other values (470) 1193
84.7%
2023-12-13T08:41:19.432777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1204
17.3%
% 1201
17.3%
3 680
9.8%
0 610
8.8%
4 515
7.4%
5 502
7.2%
1 402
 
5.8%
2 386
 
5.6%
7 282
 
4.1%
6 271
 
3.9%
Other values (14) 901
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4183
60.2%
Other Punctuation 2545
36.6%
Space Separator 74
 
1.1%
Other Letter 72
 
1.0%
Dash Punctuation 70
 
1.0%
Math Symbol 9
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 680
16.3%
0 610
14.6%
4 515
12.3%
5 502
12.0%
1 402
9.6%
2 386
9.2%
7 282
6.7%
6 271
 
6.5%
9 269
 
6.4%
8 266
 
6.4%
Other Letter
ValueCountFrequency (%)
18
25.0%
18
25.0%
9
12.5%
9
12.5%
9
12.5%
9
12.5%
Other Punctuation
ValueCountFrequency (%)
. 1204
47.3%
% 1201
47.2%
" 70
 
2.8%
, 70
 
2.8%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6882
99.0%
Hangul 72
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1204
17.5%
% 1201
17.5%
3 680
9.9%
0 610
8.9%
4 515
7.5%
5 502
7.3%
1 402
 
5.8%
2 386
 
5.6%
7 282
 
4.1%
6 271
 
3.9%
Other values (8) 829
12.0%
Hangul
ValueCountFrequency (%)
18
25.0%
18
25.0%
9
12.5%
9
12.5%
9
12.5%
9
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6882
99.0%
Hangul 72
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1204
17.5%
% 1201
17.5%
3 680
9.9%
0 610
8.9%
4 515
7.5%
5 502
7.3%
1 402
 
5.8%
2 386
 
5.6%
7 282
 
4.1%
6 271
 
3.9%
Other values (8) 829
12.0%
Hangul
ValueCountFrequency (%)
18
25.0%
18
25.0%
9
12.5%
9
12.5%
9
12.5%
9
12.5%

발행만기일
Text

MISSING 

Distinct1033
Distinct (%)77.3%
Missing2263
Missing (%)62.9%
Memory size28.3 KiB
2023-12-13T08:41:19.679373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length10
Mean length9.6858639
Min length1

Characters and Unicode

Total characters12950
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique844 ?
Unique (%)63.1%

Sample

1st row2000-10-07
2nd row2001-01-07
3rd row2001-04-07
4th row2001-10-07
5th row2002-04-07
ValueCountFrequency (%)
67
 
4.6%
000 51
 
3.5%
0 36
 
2.5%
2 7
 
0.5%
20 5
 
0.3%
2012-09-29 5
 
0.3%
2032-11-01 4
 
0.3%
2014-10-25 4
 
0.3%
2047-12-25 4
 
0.3%
2018-11-24 4
 
0.3%
Other values (1036) 1267
87.1%
2023-12-13T08:41:20.061388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2994
23.1%
2 2563
19.8%
- 2448
18.9%
1 1696
13.1%
3 681
 
5.3%
7 446
 
3.4%
9 392
 
3.0%
5 370
 
2.9%
8 348
 
2.7%
4 324
 
2.5%
Other values (9) 688
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10098
78.0%
Dash Punctuation 2448
 
18.9%
Other Punctuation 279
 
2.2%
Space Separator 121
 
0.9%
Control 2
 
< 0.1%
Other Letter 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2994
29.6%
2 2563
25.4%
1 1696
16.8%
3 681
 
6.7%
7 446
 
4.4%
9 392
 
3.9%
5 370
 
3.7%
8 348
 
3.4%
4 324
 
3.2%
6 284
 
2.8%
Other Punctuation
ValueCountFrequency (%)
" 130
46.6%
, 94
33.7%
. 29
 
10.4%
% 26
 
9.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 2448
100.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12948
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2994
23.1%
2 2563
19.8%
- 2448
18.9%
1 1696
13.1%
3 681
 
5.3%
7 446
 
3.4%
9 392
 
3.0%
5 370
 
2.9%
8 348
 
2.7%
4 324
 
2.5%
Other values (7) 686
 
5.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12948
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2994
23.1%
2 2563
19.8%
- 2448
18.9%
1 1696
13.1%
3 681
 
5.3%
7 446
 
3.4%
9 392
 
3.0%
5 370
 
2.9%
8 348
 
2.7%
4 324
 
2.5%
Other values (7) 686
 
5.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

만기상환일
Text

MISSING 

Distinct406
Distinct (%)80.6%
Missing3096
Missing (%)86.0%
Memory size28.3 KiB
2023-12-13T08:41:20.274514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length10
Mean length9.4801587
Min length1

Characters and Unicode

Total characters4778
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique352 ?
Unique (%)69.8%

Sample

1st row2000-10-07
2nd row2001-01-07
3rd row2001-04-07
4th row2001-10-07
5th row2002-04-07
ValueCountFrequency (%)
47
 
8.0%
000 32
 
5.5%
0 8
 
1.4%
2014-09-11 4
 
0.7%
2012-10-02 4
 
0.7%
2 4
 
0.7%
2014-10-27 3
 
0.5%
2013-12-23 3
 
0.5%
2014-09-29 3
 
0.5%
2013-04-23 3
 
0.5%
Other values (418) 475
81.1%
2023-12-13T08:41:20.625218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1230
25.7%
- 799
16.7%
2 770
16.1%
1 651
13.6%
3 256
 
5.4%
9 147
 
3.1%
4 143
 
3.0%
7 132
 
2.8%
8 112
 
2.3%
5 109
 
2.3%
Other values (18) 429
 
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3627
75.9%
Dash Punctuation 799
 
16.7%
Other Punctuation 245
 
5.1%
Space Separator 91
 
1.9%
Other Letter 15
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
2
13.3%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
Decimal Number
ValueCountFrequency (%)
0 1230
33.9%
2 770
21.2%
1 651
17.9%
3 256
 
7.1%
9 147
 
4.1%
4 143
 
3.9%
7 132
 
3.6%
8 112
 
3.1%
5 109
 
3.0%
6 77
 
2.1%
Other Punctuation
ValueCountFrequency (%)
" 83
33.9%
, 69
28.2%
. 47
19.2%
% 46
18.8%
Dash Punctuation
ValueCountFrequency (%)
- 799
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4763
99.7%
Hangul 15
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1230
25.8%
- 799
16.8%
2 770
16.2%
1 651
13.7%
3 256
 
5.4%
9 147
 
3.1%
4 143
 
3.0%
7 132
 
2.8%
8 112
 
2.4%
5 109
 
2.3%
Other values (7) 414
 
8.7%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
2
13.3%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4763
99.7%
Hangul 15
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1230
25.8%
- 799
16.8%
2 770
16.2%
1 651
13.7%
3 256
 
5.4%
9 147
 
3.1%
4 143
 
3.0%
7 132
 
2.8%
8 112
 
2.4%
5 109
 
2.3%
Other values (7) 414
 
8.7%
Hangul
ValueCountFrequency (%)
2
13.3%
2
13.3%
2
13.3%
2
13.3%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%
1
6.7%

만기상환금액
Text

MISSING 

Distinct249
Distinct (%)52.3%
Missing3124
Missing (%)86.8%
Memory size28.3 KiB
2023-12-13T08:41:20.929797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length14
Mean length12.69958
Min length1

Characters and Unicode

Total characters6045
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)41.6%

Sample

1st row22,000,000,000
2nd row10,000,000,000
3rd row12,000,000,000
4th row27,000,000,000
5th row33,000,000,000
ValueCountFrequency (%)
50,000,000,000 52
 
9.6%
40,000,000,000 32
 
5.9%
28
 
5.1%
60,000,000,000 18
 
3.3%
0 14
 
2.6%
80,000,000,000 13
 
2.4%
30,000,000,000 12
 
2.2%
000 12
 
2.2%
90,000,000,000 10
 
1.8%
70,000,000,000 9
 
1.7%
Other values (255) 344
63.2%
2023-12-13T08:41:21.388101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3467
57.4%
, 1134
 
18.8%
1 202
 
3.3%
2 198
 
3.3%
5 148
 
2.4%
3 144
 
2.4%
- 116
 
1.9%
4 113
 
1.9%
6 96
 
1.6%
7 81
 
1.3%
Other values (14) 346
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4584
75.8%
Other Punctuation 1254
 
20.7%
Dash Punctuation 116
 
1.9%
Space Separator 77
 
1.3%
Other Letter 12
 
0.2%
Control 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3467
75.6%
1 202
 
4.4%
2 198
 
4.3%
5 148
 
3.2%
3 144
 
3.1%
4 113
 
2.5%
6 96
 
2.1%
7 81
 
1.8%
8 73
 
1.6%
9 62
 
1.4%
Other Letter
ValueCountFrequency (%)
3
25.0%
3
25.0%
2
16.7%
2
16.7%
1
 
8.3%
1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 1134
90.4%
" 69
 
5.5%
. 26
 
2.1%
% 24
 
1.9%
? 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Space Separator
ValueCountFrequency (%)
77
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6033
99.8%
Hangul 12
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3467
57.5%
, 1134
 
18.8%
1 202
 
3.3%
2 198
 
3.3%
5 148
 
2.5%
3 144
 
2.4%
- 116
 
1.9%
4 113
 
1.9%
6 96
 
1.6%
7 81
 
1.3%
Other values (8) 334
 
5.5%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
2
16.7%
2
16.7%
1
 
8.3%
1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6033
99.8%
Hangul 12
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3467
57.5%
, 1134
 
18.8%
1 202
 
3.3%
2 198
 
3.3%
5 148
 
2.5%
3 144
 
2.4%
- 116
 
1.9%
4 113
 
1.9%
6 96
 
1.6%
7 81
 
1.3%
Other values (8) 334
 
5.5%
Hangul
ValueCountFrequency (%)
3
25.0%
3
25.0%
2
16.7%
2
16.7%
1
 
8.3%
1
 
8.3%
Distinct947
Distinct (%)39.3%
Missing1192
Missing (%)33.1%
Memory size28.3 KiB
2023-12-13T08:41:21.651617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length10
Mean length9.9098837
Min length1

Characters and Unicode

Total characters23863
Distinct characters17
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique538 ?
Unique (%)22.3%

Sample

1st row2005-10-07
2nd row2003-03-03
3rd row2003-09-01
4th row2004-03-02
5th row2004-09-01
ValueCountFrequency (%)
33
 
1.3%
0 30
 
1.2%
2013-11-25 29
 
1.2%
2013-08-26 28
 
1.1%
2014-05-25 26
 
1.0%
2013-03-25 25
 
1.0%
2014-10-27 25
 
1.0%
2013-02-25 25
 
1.0%
2014-08-25 24
 
1.0%
2013-05-25 24
 
1.0%
Other values (955) 2221
89.2%
2023-12-13T08:41:22.026954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5450
22.8%
2 4848
20.3%
- 4679
19.6%
1 3752
15.7%
3 1141
 
4.8%
5 1008
 
4.2%
4 917
 
3.8%
6 488
 
2.0%
7 479
 
2.0%
8 450
 
1.9%
Other values (7) 651
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18947
79.4%
Dash Punctuation 4679
 
19.6%
Other Punctuation 150
 
0.6%
Space Separator 86
 
0.4%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5450
28.8%
2 4848
25.6%
1 3752
19.8%
3 1141
 
6.0%
5 1008
 
5.3%
4 917
 
4.8%
6 488
 
2.6%
7 479
 
2.5%
8 450
 
2.4%
9 414
 
2.2%
Other Punctuation
ValueCountFrequency (%)
" 86
57.3%
, 52
34.7%
. 6
 
4.0%
% 6
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 4679
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23863
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5450
22.8%
2 4848
20.3%
- 4679
19.6%
1 3752
15.7%
3 1141
 
4.8%
5 1008
 
4.2%
4 917
 
3.8%
6 488
 
2.0%
7 479
 
2.0%
8 450
 
1.9%
Other values (7) 651
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23863
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5450
22.8%
2 4848
20.3%
- 4679
19.6%
1 3752
15.7%
3 1141
 
4.8%
5 1008
 
4.2%
4 917
 
3.8%
6 488
 
2.0%
7 479
 
2.0%
8 450
 
1.9%
Other values (7) 651
 
2.7%
Distinct1073
Distinct (%)44.7%
Missing1202
Missing (%)33.4%
Memory size28.3 KiB
2023-12-13T08:41:22.272482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length13.067139
Min length1

Characters and Unicode

Total characters31335
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique759 ?
Unique (%)31.7%

Sample

1st row19,000,000,000
2nd row35,000,000,000
3rd row34,000,000,000
4th row32,000,000,000
5th row35,000,000,000
ValueCountFrequency (%)
53
 
2.1%
3,000,000,000 51
 
2.0%
12,000,000,000 51
 
2.0%
0 48
 
1.9%
4,000,000,000 36
 
1.4%
8,000,000,000 36
 
1.4%
11,000,000,000 35
 
1.4%
5,000,000,000 35
 
1.4%
6,000,000,000 34
 
1.4%
10,000,000,000 31
 
1.2%
Other values (1068) 2085
83.6%
2023-12-13T08:41:22.666166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17855
57.0%
, 6841
 
21.8%
1 1100
 
3.5%
2 942
 
3.0%
5 824
 
2.6%
3 732
 
2.3%
4 691
 
2.2%
6 593
 
1.9%
8 508
 
1.6%
7 496
 
1.6%
Other values (9) 753
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24206
77.2%
Other Punctuation 6950
 
22.2%
Space Separator 150
 
0.5%
Dash Punctuation 24
 
0.1%
Other Letter 4
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17855
73.8%
1 1100
 
4.5%
2 942
 
3.9%
5 824
 
3.4%
3 732
 
3.0%
4 691
 
2.9%
6 593
 
2.4%
8 508
 
2.1%
7 496
 
2.0%
9 465
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 6841
98.4%
" 101
 
1.5%
. 5
 
0.1%
% 3
 
< 0.1%
Other Letter
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31331
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17855
57.0%
, 6841
 
21.8%
1 1100
 
3.5%
2 942
 
3.0%
5 824
 
2.6%
3 732
 
2.3%
4 691
 
2.2%
6 593
 
1.9%
8 508
 
1.6%
7 496
 
1.6%
Other values (7) 749
 
2.4%
Hangul
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31331
> 99.9%
Hangul 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17855
57.0%
, 6841
 
21.8%
1 1100
 
3.5%
2 942
 
3.0%
5 824
 
2.6%
3 732
 
2.3%
4 691
 
2.2%
6 593
 
1.9%
8 508
 
1.6%
7 496
 
1.6%
Other values (7) 749
 
2.4%
Hangul
ValueCountFrequency (%)
2
50.0%
2
50.0%

상환합계
Text

MISSING 

Distinct1162
Distinct (%)33.9%
Missing171
Missing (%)4.8%
Memory size28.3 KiB
2023-12-13T08:41:22.878690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length55
Mean length10.737241
Min length1

Characters and Unicode

Total characters36818
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique814 ?
Unique (%)23.7%

Sample

1st row22,000,000,000
2nd row10,000,000,000
3rd row12,000,000,000
4th row27,000,000,000
5th row33,000,000,000
ValueCountFrequency (%)
0 727
 
20.3%
84
 
2.3%
12,000,000,000 54
 
1.5%
3,000,000,000 51
 
1.4%
50,000,000,000 49
 
1.4%
000 40
 
1.1%
40,000,000,000 39
 
1.1%
8,000,000,000 37
 
1.0%
5,000,000,000 36
 
1.0%
4,000,000,000 36
 
1.0%
Other values (1159) 2428
67.8%
2023-12-13T08:41:23.206017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21546
58.5%
, 7825
 
21.3%
1 1201
 
3.3%
2 1028
 
2.8%
5 919
 
2.5%
3 812
 
2.2%
4 757
 
2.1%
6 652
 
1.8%
8 555
 
1.5%
7 548
 
1.5%
Other values (9) 975
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28524
77.5%
Other Punctuation 7999
 
21.7%
Space Separator 205
 
0.6%
Dash Punctuation 54
 
0.1%
Other Letter 30
 
0.1%
Control 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21546
75.5%
1 1201
 
4.2%
2 1028
 
3.6%
5 919
 
3.2%
3 812
 
2.8%
4 757
 
2.7%
6 652
 
2.3%
8 555
 
1.9%
7 548
 
1.9%
9 506
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 7825
97.8%
" 144
 
1.8%
. 16
 
0.2%
% 14
 
0.2%
Other Letter
ValueCountFrequency (%)
15
50.0%
15
50.0%
Space Separator
ValueCountFrequency (%)
205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36788
99.9%
Hangul 30
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21546
58.6%
, 7825
 
21.3%
1 1201
 
3.3%
2 1028
 
2.8%
5 919
 
2.5%
3 812
 
2.2%
4 757
 
2.1%
6 652
 
1.8%
8 555
 
1.5%
7 548
 
1.5%
Other values (7) 945
 
2.6%
Hangul
ValueCountFrequency (%)
15
50.0%
15
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36788
99.9%
Hangul 30
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21546
58.6%
, 7825
 
21.3%
1 1201
 
3.3%
2 1028
 
2.8%
5 919
 
2.5%
3 812
 
2.2%
4 757
 
2.1%
6 652
 
1.8%
8 555
 
1.5%
7 548
 
1.5%
Other values (7) 945
 
2.6%
Hangul
ValueCountFrequency (%)
15
50.0%
15
50.0%

잔액트랜치
Text

MISSING 

Distinct56
Distinct (%)4.4%
Missing2338
Missing (%)64.9%
Memory size28.3 KiB
2023-12-13T08:41:23.421326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length255
Median length5
Mean length11.090333
Min length2

Characters and Unicode

Total characters13996
Distinct characters18
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)2.9%

Sample

1st row02-01
2nd row02-02
3rd row01-11
4th row02-01
5th row02-02
ValueCountFrequency (%)
01-01 137
10.2%
02-01 130
9.7%
01-03 126
9.4%
01-05 122
9.1%
01-04 120
9.0%
01-02 117
8.7%
01-06 115
8.6%
01-07 106
7.9%
01-08 105
7.8%
86
6.4%
Other values (56) 174
13.0%
2023-12-13T08:41:23.808464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
# 7140
51.0%
0 2710
 
19.4%
1 1419
 
10.1%
- 1266
 
9.0%
2 314
 
2.2%
3 154
 
1.1%
5 137
 
1.0%
4 131
 
0.9%
6 123
 
0.9%
7 121
 
0.9%
Other values (8) 481
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 7337
52.4%
Decimal Number 5301
37.9%
Dash Punctuation 1266
 
9.0%
Space Separator 86
 
0.6%
Control 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2710
51.1%
1 1419
26.8%
2 314
 
5.9%
3 154
 
2.9%
5 137
 
2.6%
4 131
 
2.5%
6 123
 
2.3%
7 121
 
2.3%
8 112
 
2.1%
9 80
 
1.5%
Other Punctuation
ValueCountFrequency (%)
# 7140
97.3%
, 96
 
1.3%
" 82
 
1.1%
. 10
 
0.1%
% 9
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1266
100.0%
Space Separator
ValueCountFrequency (%)
86
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
# 7140
51.0%
0 2710
 
19.4%
1 1419
 
10.1%
- 1266
 
9.0%
2 314
 
2.2%
3 154
 
1.1%
5 137
 
1.0%
4 131
 
0.9%
6 123
 
0.9%
7 121
 
0.9%
Other values (8) 481
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
# 7140
51.0%
0 2710
 
19.4%
1 1419
 
10.1%
- 1266
 
9.0%
2 314
 
2.2%
3 154
 
1.1%
5 137
 
1.0%
4 131
 
0.9%
6 123
 
0.9%
7 121
 
0.9%
Other values (8) 481
 
3.4%

잔액이율
Text

MISSING 

Distinct495
Distinct (%)39.1%
Missing2333
Missing (%)64.8%
Memory size28.3 KiB
2023-12-13T08:41:24.154435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length5
Mean length5.6819258
Min length1

Characters and Unicode

Total characters7199
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)18.2%

Sample

1st row2.00%
2nd row2.00%
3rd row9.00%
4th row6.00%
5th row7.00%
ValueCountFrequency (%)
55
 
3.9%
0 39
 
2.8%
01월 28
 
2.0%
000 22
 
1.6%
3.02 10
 
0.7%
3.76 10
 
0.7%
3.14 10
 
0.7%
3.22 9
 
0.6%
4.00 9
 
0.6%
01일 9
 
0.6%
Other values (497) 1202
85.7%
2023-12-13T08:41:24.634316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1090
15.1%
% 1088
15.1%
0 867
12.0%
3 638
8.9%
4 520
7.2%
5 471
6.5%
1 456
6.3%
2 420
 
5.8%
6 272
 
3.8%
9 264
 
3.7%
Other values (15) 1113
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4400
61.1%
Other Punctuation 2453
34.1%
Space Separator 157
 
2.2%
Dash Punctuation 97
 
1.3%
Other Letter 82
 
1.1%
Control 7
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 867
19.7%
3 638
14.5%
4 520
11.8%
5 471
10.7%
1 456
10.4%
2 420
9.5%
6 272
 
6.2%
9 264
 
6.0%
7 252
 
5.7%
8 240
 
5.5%
Other Letter
ValueCountFrequency (%)
34
41.5%
34
41.5%
3
 
3.7%
3
 
3.7%
3
 
3.7%
3
 
3.7%
2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 1090
44.4%
% 1088
44.4%
, 176
 
7.2%
" 99
 
4.0%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7117
98.9%
Hangul 82
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1090
15.3%
% 1088
15.3%
0 867
12.2%
3 638
9.0%
4 520
7.3%
5 471
6.6%
1 456
6.4%
2 420
 
5.9%
6 272
 
3.8%
9 264
 
3.7%
Other values (8) 1031
14.5%
Hangul
ValueCountFrequency (%)
34
41.5%
34
41.5%
3
 
3.7%
3
 
3.7%
3
 
3.7%
3
 
3.7%
2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7117
98.9%
Hangul 82
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1090
15.3%
% 1088
15.3%
0 867
12.2%
3 638
9.0%
4 520
7.3%
5 471
6.6%
1 456
6.4%
2 420
 
5.9%
6 272
 
3.8%
9 264
 
3.7%
Other values (8) 1031
14.5%
Hangul
ValueCountFrequency (%)
34
41.5%
34
41.5%
3
 
3.7%
3
 
3.7%
3
 
3.7%
3
 
3.7%
2
 
2.4%

반액만기일
Text

MISSING 

Distinct1019
Distinct (%)80.3%
Missing2331
Missing (%)64.8%
Memory size28.3 KiB
2023-12-13T08:41:24.912183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length10
Mean length9.6241135
Min length1

Characters and Unicode

Total characters12213
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique853 ?
Unique (%)67.2%

Sample

1st row2006-04-07
2nd row2007-04-07
3rd row2008-03-01
4th row2008-09-01
5th row2009-09-01
ValueCountFrequency (%)
0 45
 
3.3%
34
 
2.5%
01월 25
 
1.8%
000 16
 
1.2%
02일 5
 
0.4%
2012-09-29 5
 
0.4%
2 5
 
0.4%
01일 5
 
0.4%
2047-12-25 4
 
0.3%
10,000,000,000 4
 
0.3%
Other values (1024) 1226
89.2%
2023-12-13T08:41:25.285512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2938
24.1%
2 2316
19.0%
- 2183
17.9%
1 1577
12.9%
3 632
 
5.2%
7 422
 
3.5%
9 375
 
3.1%
5 357
 
2.9%
8 320
 
2.6%
4 296
 
2.4%
Other values (10) 797
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9513
77.9%
Dash Punctuation 2183
 
17.9%
Other Punctuation 339
 
2.8%
Space Separator 115
 
0.9%
Other Letter 54
 
0.4%
Control 9
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2938
30.9%
2 2316
24.3%
1 1577
16.6%
3 632
 
6.6%
7 422
 
4.4%
9 375
 
3.9%
5 357
 
3.8%
8 320
 
3.4%
4 296
 
3.1%
6 280
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 178
52.5%
" 84
24.8%
% 39
 
11.5%
. 38
 
11.2%
Other Letter
ValueCountFrequency (%)
26
48.1%
26
48.1%
2
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 2183
100.0%
Space Separator
ValueCountFrequency (%)
115
100.0%
Control
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12159
99.6%
Hangul 54
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2938
24.2%
2 2316
19.0%
- 2183
18.0%
1 1577
13.0%
3 632
 
5.2%
7 422
 
3.5%
9 375
 
3.1%
5 357
 
2.9%
8 320
 
2.6%
4 296
 
2.4%
Other values (7) 743
 
6.1%
Hangul
ValueCountFrequency (%)
26
48.1%
26
48.1%
2
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12159
99.6%
Hangul 54
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2938
24.2%
2 2316
19.0%
- 2183
18.0%
1 1577
13.0%
3 632
 
5.2%
7 422
 
3.5%
9 375
 
3.1%
5 357
 
2.9%
8 320
 
2.6%
4 296
 
2.4%
Other values (7) 743
 
6.1%
Hangul
ValueCountFrequency (%)
26
48.1%
26
48.1%
2
 
3.7%

원금잔액
Text

MISSING 

Distinct251
Distinct (%)19.6%
Missing2317
Missing (%)64.4%
Memory size28.3 KiB
2023-12-13T08:41:25.492082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length32
Mean length7.2143414
Min length1

Characters and Unicode

Total characters9256
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)14.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 595
43.5%
10,000,000,000 103
 
7.5%
40
 
2.9%
30,000,000,000 26
 
1.9%
50,000,000,000 24
 
1.8%
000 24
 
1.8%
40,000,000,000 23
 
1.7%
60,000,000,000 20
 
1.5%
10,000,000 19
 
1.4%
80,000,000,000 18
 
1.3%
Other values (249) 475
34.7%
2023-12-13T08:41:25.821753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5903
63.8%
, 1651
 
17.8%
1 423
 
4.6%
2 215
 
2.3%
3 149
 
1.6%
5 118
 
1.3%
4 110
 
1.2%
104
 
1.1%
- 93
 
1.0%
7 92
 
1.0%
Other values (9) 398
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7231
78.1%
Other Punctuation 1787
 
19.3%
Space Separator 104
 
1.1%
Dash Punctuation 93
 
1.0%
Other Letter 36
 
0.4%
Control 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5903
81.6%
1 423
 
5.8%
2 215
 
3.0%
3 149
 
2.1%
5 118
 
1.6%
4 110
 
1.5%
7 92
 
1.3%
9 80
 
1.1%
8 76
 
1.1%
6 65
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 1651
92.4%
" 74
 
4.1%
. 31
 
1.7%
% 31
 
1.7%
Other Letter
ValueCountFrequency (%)
18
50.0%
18
50.0%
Space Separator
ValueCountFrequency (%)
104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Control
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9220
99.6%
Hangul 36
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5903
64.0%
, 1651
 
17.9%
1 423
 
4.6%
2 215
 
2.3%
3 149
 
1.6%
5 118
 
1.3%
4 110
 
1.2%
104
 
1.1%
- 93
 
1.0%
7 92
 
1.0%
Other values (7) 362
 
3.9%
Hangul
ValueCountFrequency (%)
18
50.0%
18
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9220
99.6%
Hangul 36
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5903
64.0%
, 1651
 
17.9%
1 423
 
4.6%
2 215
 
2.3%
3 149
 
1.6%
5 118
 
1.3%
4 110
 
1.2%
104
 
1.1%
- 93
 
1.0%
7 92
 
1.0%
Other values (7) 362
 
3.9%
Hangul
ValueCountFrequency (%)
18
50.0%
18
50.0%

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3600
Missing (%)100.0%
Memory size31.8 KiB

Unnamed: 15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3599
Missing (%)> 99.9%
Memory size28.3 KiB
2023-12-13T08:41:25.954142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row60,000,000,000
ValueCountFrequency (%)
60,000,000,000 1
100.0%
2023-12-13T08:41:26.191414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
71.4%
, 3
 
21.4%
6 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
78.6%
Other Punctuation 3
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
90.9%
6 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
71.4%
, 3
 
21.4%
6 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
71.4%
, 3
 
21.4%
6 1
 
7.1%

Unnamed: 16
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3599
Missing (%)> 99.9%
Memory size28.3 KiB
2023-12-13T08:41:26.336517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row01월 02일
ValueCountFrequency (%)
01월 1
50.0%
02일 1
50.0%
2023-12-13T08:41:26.586836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
28.6%
1 1
14.3%
1
14.3%
1
14.3%
2 1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
57.1%
Other Letter 2
28.6%
Space Separator 1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
2 1
25.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
71.4%
Hangul 2
 
28.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
40.0%
1 1
20.0%
1
20.0%
2 1
20.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
71.4%
Hangul 2
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
40.0%
1 1
20.0%
1
20.0%
2 1
20.0%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 17
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3599
Missing (%)> 99.9%
Memory size28.3 KiB
2023-12-13T08:41:26.708872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
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

Unique1 ?
Unique (%)100.0%

Sample

1st row3.48%
ValueCountFrequency (%)
3.48 1
100.0%
2023-12-13T08:41:26.902646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1
20.0%
. 1
20.0%
4 1
20.0%
8 1
20.0%
% 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
60.0%
Other Punctuation 2
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
33.3%
4 1
33.3%
8 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
% 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1
20.0%
. 1
20.0%
4 1
20.0%
8 1
20.0%
% 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1
20.0%
. 1
20.0%
4 1
20.0%
8 1
20.0%
% 1
20.0%

Unnamed: 18
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3599
Missing (%)> 99.9%
Memory size28.3 KiB
Minimum2014-06-21 00:00:00
Maximum2014-06-21 00:00:00
2023-12-13T08:41:27.018401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:41:27.124655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 19
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3599
Missing (%)> 99.9%
Memory size28.3 KiB
2023-12-13T08:41:27.243712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters20
Distinct characters11
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row" , 2012-14,1-3," 60
ValueCountFrequency (%)
2
50.0%
2012-14,1-3 1
25.0%
60 1
25.0%
2023-12-13T08:41:27.490059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3
15.0%
1 3
15.0%
" 2
10.0%
2
10.0%
2 2
10.0%
0 2
10.0%
- 2
10.0%
1
 
5.0%
4 1
 
5.0%
3 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
50.0%
Other Punctuation 5
25.0%
Space Separator 2
 
10.0%
Dash Punctuation 2
 
10.0%
Control 1
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
0 2
20.0%
4 1
 
10.0%
3 1
 
10.0%
6 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
" 2
40.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3
15.0%
1 3
15.0%
" 2
10.0%
2
10.0%
2 2
10.0%
0 2
10.0%
- 2
10.0%
1
 
5.0%
4 1
 
5.0%
3 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3
15.0%
1 3
15.0%
" 2
10.0%
2
10.0%
2 2
10.0%
0 2
10.0%
- 2
10.0%
1
 
5.0%
4 1
 
5.0%
3 1
 
5.0%

Unnamed: 20
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.3 KiB
<NA>
3599 
0
 
1

Length

Max length4
Median length4
Mean length3.9991667
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3599
> 99.9%
0 1
 
< 0.1%

Length

2023-12-13T08:41:27.659272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:41:27.763329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3599
> 99.9%
0 1
 
< 0.1%

Sample

풀명트랜치명발행금액발행이율발행만기일만기상환일만기상환금액콜옵션행사상환일콜옵션행사상환금액상환합계잔액트랜치잔액이율반액만기일원금잔액Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20
0Jan-0001-0122,000,000,0008.15%2000-10-072000-10-0722,000,000,000<NA><NA>22,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
1Jan-0001-0210,000,000,0008.57%2001-01-072001-01-0710,000,000,000<NA><NA>10,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
2Jan-0001-0312,000,000,0008.81%2001-04-072001-04-0712,000,000,000<NA><NA>12,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
3Jan-0001-0427,000,000,0009.01%2001-10-072001-10-0727,000,000,000<NA><NA>27,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
4Jan-0001-0533,000,000,0009.16%2002-04-072002-04-0733,000,000,000<NA><NA>33,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
5Jan-0001-0679,000,000,0009.39%2003-04-072003-04-0779,000,000,000<NA><NA>79,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
6Jan-0001-0792,000,000,0009.69%2004-04-072004-04-0792,000,000,000<NA><NA>92,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
7Jan-0001-0875,000,000,0009.94%2005-04-072005-04-0775,000,000,000<NA><NA>75,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
8Jan-0001-0919,000,000,00010.04%2006-04-07<NA><NA>2005-10-0719,000,000,00019,000,000,000<NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA>
9Jan-0002-0119,600,000,0002.00%2006-04-072006-04-1119,600,000,000<NA><NA>19,600,000,00002-012.00%2006-04-070<NA><NA><NA><NA><NA><NA><NA>
풀명트랜치명발행금액발행이율발행만기일만기상환일만기상환금액콜옵션행사상환일콜옵션행사상환금액상환합계잔액트랜치잔액이율반액만기일원금잔액Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20
35902011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35912011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35922011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35932011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35942011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35952011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35962011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35972011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35982011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35992011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

풀명트랜치명발행금액발행이율발행만기일만기상환일만기상환금액콜옵션행사상환일콜옵션행사상환금액상환합계잔액트랜치잔액이율반액만기일원금잔액Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20# duplicates
922011-19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>13
0002-01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>10
2409-Oct<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8
1162012-18<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>8
1609-Dec<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7
5812-Jun<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>7
1062012-14<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
1092012-15<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
1802012-40<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
2510-Apr<NA><NA><NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5