Overview

Dataset statistics

Number of variables17
Number of observations967
Missing cells1337
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.3 KiB
Average record size in memory140.1 B

Variable types

Categorical4
Text8
Numeric2
Boolean1
DateTime2

Dataset

Description한국사학진흥재단에서 진행되었던 연수에 대한 연수 진행시 수납 금액 및 연수 취소시 해당 사유, 환불 담당자, 금액 등에 대한 관리 정보
Author한국사학진흥재단
URLhttps://www.data.go.kr/data/15042683/fileData.do

Alerts

적용여부 has constant value ""Constant
수정자 is highly overall correlated with 연수번호 and 1 other fieldsHigh correlation
연수번호 is highly overall correlated with 수정자 and 1 other fieldsHigh correlation
Unnamed: 16 is highly overall correlated with 연수번호 and 1 other fieldsHigh correlation
순번 is highly imbalanced (85.5%)Imbalance
Unnamed: 16 is highly imbalanced (95.6%)Imbalance
적용여부 has 20 (2.1%) missing valuesMissing
전표번호 has 22 (2.3%) missing valuesMissing
수정일자 has 22 (2.3%) missing valuesMissing
통장사본 has 358 (37.0%) missing valuesMissing
환불개인통장 반환사유 has 915 (94.6%) missing valuesMissing
환불요청금액 has 48 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-17 09:20:50.671239
Analysis finished2024-04-17 09:20:52.418145
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연수번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2020000000000000
670 
2010000000000000
297 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2010000000000000
2nd row2010000000000000
3rd row2010000000000000
4th row2010000000000000
5th row2010000000000000

Common Values

ValueCountFrequency (%)
2020000000000000 670
69.3%
2010000000000000 297
30.7%

Length

2024-04-17T18:20:52.466269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:20:52.538552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020000000000000 670
69.3%
2010000000000000 297
30.7%

사용자아이디
Text

Distinct876
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-17T18:20:52.784474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.7880041
Min length4

Characters and Unicode

Total characters7531
Distinct characters39
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

Unique796 ?
Unique (%)82.3%

Sample

1st rowejlee
2nd rowsjee22
3rd rowrlarse
4th rowskhumhchung
5th rowgkswjddms
ValueCountFrequency (%)
kbae0e 4
 
0.4%
seoilkim 3
 
0.3%
kimjh 3
 
0.3%
bluellroca 3
 
0.3%
tm0880 3
 
0.3%
soojung126 3
 
0.3%
kmj486 3
 
0.3%
sam12250 3
 
0.3%
pknush 3
 
0.3%
d154250 3
 
0.3%
Other values (866) 936
96.8%
2024-04-17T18:20:53.170669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 444
 
5.9%
s 428
 
5.7%
o 403
 
5.4%
a 397
 
5.3%
e 386
 
5.1%
0 377
 
5.0%
1 343
 
4.6%
i 324
 
4.3%
2 307
 
4.1%
k 299
 
4.0%
Other values (29) 3823
50.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5436
72.2%
Decimal Number 2088
 
27.7%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 444
 
8.2%
s 428
 
7.9%
o 403
 
7.4%
a 397
 
7.3%
e 386
 
7.1%
i 324
 
6.0%
k 299
 
5.5%
h 287
 
5.3%
j 270
 
5.0%
u 237
 
4.4%
Other values (16) 1961
36.1%
Decimal Number
ValueCountFrequency (%)
0 377
18.1%
1 343
16.4%
2 307
14.7%
7 189
9.1%
9 177
8.5%
5 163
7.8%
3 157
7.5%
4 128
 
6.1%
8 124
 
5.9%
6 123
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
D 3
42.9%
M 2
28.6%
K 2
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 5443
72.3%
Common 2088
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 444
 
8.2%
s 428
 
7.9%
o 403
 
7.4%
a 397
 
7.3%
e 386
 
7.1%
i 324
 
6.0%
k 299
 
5.5%
h 287
 
5.3%
j 270
 
5.0%
u 237
 
4.4%
Other values (19) 1968
36.2%
Common
ValueCountFrequency (%)
0 377
18.1%
1 343
16.4%
2 307
14.7%
7 189
9.1%
9 177
8.5%
5 163
7.8%
3 157
7.5%
4 128
 
6.1%
8 124
 
5.9%
6 123
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 444
 
5.9%
s 428
 
5.7%
o 403
 
5.4%
a 397
 
5.3%
e 386
 
5.1%
0 377
 
5.0%
1 343
 
4.6%
i 324
 
4.3%
2 307
 
4.1%
k 299
 
4.0%
Other values (29) 3823
50.8%

순번
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
1
947 
2
 
20

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 (%)
1 947
97.9%
2 20
 
2.1%

Length

2024-04-17T18:20:53.299623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:20:53.375549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 947
97.9%
2 20
 
2.1%

수납은행코드
Real number (ℝ)

Distinct22
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.648397
Minimum1
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2024-04-17T18:20:53.447674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median20
Q337
95-th percentile88
Maximum88
Range87
Interquartile range (IQR)26

Descriptive statistics

Standard deviation29.706997
Coefficient of variation (CV)0.96928386
Kurtosis-0.44882449
Mean30.648397
Median Absolute Deviation (MAD)14
Skewness1.0397236
Sum29637
Variance882.50565
MonotonicityNot monotonic
2024-04-17T18:20:53.548041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
11 170
17.6%
20 152
15.7%
4 137
14.2%
88 109
11.3%
81 89
9.2%
3 76
7.9%
31 48
 
5.0%
34 38
 
3.9%
32 35
 
3.6%
12 21
 
2.2%
Other values (12) 92
9.5%
ValueCountFrequency (%)
1 2
 
0.2%
3 76
7.9%
4 137
14.2%
5 6
 
0.6%
7 5
 
0.5%
11 170
17.6%
12 21
 
2.2%
20 152
15.7%
23 11
 
1.1%
26 12
 
1.2%
ValueCountFrequency (%)
88 109
11.3%
81 89
9.2%
71 5
 
0.5%
48 4
 
0.4%
45 7
 
0.7%
39 18
 
1.9%
37 20
 
2.1%
35 1
 
0.1%
34 38
 
3.9%
32 35
 
3.6%

환불요청금액
Real number (ℝ)

ZEROS 

Distinct86
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean310056.57
Minimum0
Maximum940000
Zeros48
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2024-04-17T18:20:53.657715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1250000
median340000
Q3430000
95-th percentile508200
Maximum940000
Range940000
Interquartile range (IQR)180000

Descriptive statistics

Standard deviation145766.54
Coefficient of variation (CV)0.47012885
Kurtosis-0.068560607
Mean310056.57
Median Absolute Deviation (MAD)90000
Skewness-0.44637197
Sum2.998247 × 108
Variance2.1247883 × 1010
MonotonicityNot monotonic
2024-04-17T18:20:53.764982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250000 118
 
12.2%
440000 98
 
10.1%
380000 93
 
9.6%
270000 77
 
8.0%
0 48
 
5.0%
120000 41
 
4.2%
352000 32
 
3.3%
470000 31
 
3.2%
430000 28
 
2.9%
510000 27
 
2.8%
Other values (76) 374
38.7%
ValueCountFrequency (%)
0 48
5.0%
100 2
 
0.2%
10000 9
 
0.9%
20000 6
 
0.6%
30000 2
 
0.2%
40000 5
 
0.5%
50000 4
 
0.4%
53000 1
 
0.1%
55000 2
 
0.2%
58000 1
 
0.1%
ValueCountFrequency (%)
940000 1
 
0.1%
704000 1
 
0.1%
660000 3
0.3%
630000 2
 
0.2%
610000 1
 
0.1%
590000 1
 
0.1%
580000 5
0.5%
540000 1
 
0.1%
528000 4
0.4%
520000 3
0.3%

환불담당자소속
Text

Distinct515
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-17T18:20:53.965447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length6.3784902
Min length1

Characters and Unicode

Total characters6168
Distinct characters229
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique393 ?
Unique (%)40.6%

Sample

1st row재단
2nd row산학협력단
3rd row산학협력단
4th row연구처
5th row총무처
ValueCountFrequency (%)
산학협력단 118
 
10.2%
사무처 62
 
5.4%
총무팀 41
 
3.5%
기획처 29
 
2.5%
총무처 24
 
2.1%
재무팀 20
 
1.7%
법인사무국 16
 
1.4%
총무과 16
 
1.4%
재무회계팀 14
 
1.2%
경리팀 13
 
1.1%
Other values (465) 803
69.5%
2024-04-17T18:20:54.315378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 692
 
11.2%
대 446
 
7.2%
교 427
 
6.9%
무 282
 
4.6%
산 281
 
4.6%
팀 250
 
4.1%
력 214
 
3.5%
협 210
 
3.4%
단 199
 
3.2%
196
 
3.2%
Other values (219) 2971
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5919
96.0%
Space Separator 196
 
3.2%
Uppercase Letter 24
 
0.4%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%
Other Punctuation 3
 
< 0.1%
Decimal Number 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 692
 
11.7%
대 446
 
7.5%
교 427
 
7.2%
무 282
 
4.8%
산 281
 
4.7%
팀 250
 
4.2%
력 214
 
3.6%
협 210
 
3.5%
단 199
 
3.4%
처 175
 
3.0%
Other values (195) 2743
46.3%
Uppercase Letter
ValueCountFrequency (%)
I 6
25.0%
C 4
16.7%
D 3
12.5%
N 2
 
8.3%
R 2
 
8.3%
L 2
 
8.3%
K 2
 
8.3%
E 1
 
4.2%
A 1
 
4.2%
T 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
& 1
33.3%
. 1
33.3%
/ 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
4 1
33.3%
3 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 9
90.0%
[ 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 9
90.0%
] 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5919
96.0%
Common 225
 
3.6%
Latin 24
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 692
 
11.7%
대 446
 
7.5%
교 427
 
7.2%
무 282
 
4.8%
산 281
 
4.7%
팀 250
 
4.2%
력 214
 
3.6%
협 210
 
3.5%
단 199
 
3.4%
처 175
 
3.0%
Other values (195) 2743
46.3%
Common
ValueCountFrequency (%)
196
87.1%
( 9
 
4.0%
) 9
 
4.0%
] 1
 
0.4%
[ 1
 
0.4%
& 1
 
0.4%
+ 1
 
0.4%
2 1
 
0.4%
. 1
 
0.4%
/ 1
 
0.4%
Other values (4) 4
 
1.8%
Latin
ValueCountFrequency (%)
I 6
25.0%
C 4
16.7%
D 3
12.5%
N 2
 
8.3%
R 2
 
8.3%
L 2
 
8.3%
K 2
 
8.3%
E 1
 
4.2%
A 1
 
4.2%
T 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5919
96.0%
ASCII 249
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 692
 
11.7%
대 446
 
7.5%
교 427
 
7.2%
무 282
 
4.8%
산 281
 
4.7%
팀 250
 
4.2%
력 214
 
3.6%
협 210
 
3.5%
단 199
 
3.4%
처 175
 
3.0%
Other values (195) 2743
46.3%
ASCII
ValueCountFrequency (%)
196
78.7%
( 9
 
3.6%
) 9
 
3.6%
I 6
 
2.4%
C 4
 
1.6%
D 3
 
1.2%
N 2
 
0.8%
R 2
 
0.8%
L 2
 
0.8%
K 2
 
0.8%
Other values (14) 14
 
5.6%

환불담당자직위
Text

Distinct142
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-17T18:20:54.577521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length2.4115822
Min length1

Characters and Unicode

Total characters2332
Distinct characters104
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)9.3%

Sample

1st row주임
2nd row법인직원
3rd row법인직원
4th row주임
5th row직원
ValueCountFrequency (%)
직원 247
25.4%
팀원 93
 
9.6%
담당 72
 
7.4%
팀장 70
 
7.2%
과장 66
 
6.8%
주임 62
 
6.4%
계장 39
 
4.0%
사원 36
 
3.7%
주무관 28
 
2.9%
대리 20
 
2.1%
Other values (127) 240
24.7%
2024-04-17T18:20:54.951046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 427
18.3%
직 274
11.7%
장 259
 
11.1%
팀 185
 
7.9%
주 101
 
4.3%
담 95
 
4.1%
당 95
 
4.1%
임 77
 
3.3%
무 74
 
3.2%
과 73
 
3.1%
Other values (94) 672
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2292
98.3%
Decimal Number 29
 
1.2%
Space Separator 9
 
0.4%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 427
18.6%
직 274
12.0%
장 259
11.3%
팀 185
 
8.1%
주 101
 
4.4%
담 95
 
4.1%
당 95
 
4.1%
임 77
 
3.4%
무 74
 
3.2%
과 73
 
3.2%
Other values (84) 632
27.6%
Decimal Number
ValueCountFrequency (%)
9 11
37.9%
7 6
20.7%
6 5
17.2%
8 3
 
10.3%
3 2
 
6.9%
5 1
 
3.4%
4 1
 
3.4%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2292
98.3%
Common 40
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 427
18.6%
직 274
12.0%
장 259
11.3%
팀 185
 
8.1%
주 101
 
4.4%
담 95
 
4.1%
당 95
 
4.1%
임 77
 
3.4%
무 74
 
3.2%
과 73
 
3.2%
Other values (84) 632
27.6%
Common
ValueCountFrequency (%)
9 11
27.5%
9
22.5%
7 6
15.0%
6 5
12.5%
8 3
 
7.5%
3 2
 
5.0%
- 1
 
2.5%
5 1
 
2.5%
4 1
 
2.5%
. 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2292
98.3%
ASCII 40
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 427
18.6%
직 274
12.0%
장 259
11.3%
팀 185
 
8.1%
주 101
 
4.4%
담 95
 
4.1%
당 95
 
4.1%
임 77
 
3.4%
무 74
 
3.2%
과 73
 
3.2%
Other values (84) 632
27.6%
ASCII
ValueCountFrequency (%)
9 11
27.5%
9
22.5%
7 6
15.0%
6 5
12.5%
8 3
 
7.5%
3 2
 
5.0%
- 1
 
2.5%
5 1
 
2.5%
4 1
 
2.5%
. 1
 
2.5%

환불사유
Text

Distinct692
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-17T18:20:55.270786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length44
Mean length9.1685626
Min length2

Characters and Unicode

Total characters8866
Distinct characters310
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique587 ?
Unique (%)60.7%

Sample

1st row연수취소
2nd row감사로인한 연수취소
3rd row내부사정
4th row회계감사로 인한 참가불가
5th row학교결산업무
ValueCountFrequency (%)
인한 112
 
5.0%
취소 102
 
4.6%
업무 54
 
2.4%
불참 54
 
2.4%
연수취소 46
 
2.1%
연수 44
 
2.0%
교육 34
 
1.5%
불가 32
 
1.4%
중복 32
 
1.4%
업무로 26
 
1.2%
Other values (823) 1702
76.1%
2024-04-17T18:20:55.691434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1287
 
14.5%
로 308
 
3.5%
교 269
 
3.0%
사 269
 
3.0%
인 267
 
3.0%
정 262
 
3.0%
무 229
 
2.6%
업 222
 
2.5%
소 210
 
2.4%
취 208
 
2.3%
Other values (300) 5335
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7361
83.0%
Space Separator 1287
 
14.5%
Decimal Number 101
 
1.1%
Open Punctuation 36
 
0.4%
Close Punctuation 36
 
0.4%
Other Punctuation 32
 
0.4%
Dash Punctuation 4
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Math Symbol 3
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 308
 
4.2%
교 269
 
3.7%
사 269
 
3.7%
인 267
 
3.6%
정 262
 
3.6%
무 229
 
3.1%
업 222
 
3.0%
소 210
 
2.9%
취 208
 
2.8%
불 193
 
2.6%
Other values (276) 4924
66.9%
Decimal Number
ValueCountFrequency (%)
1 47
46.5%
9 28
27.7%
2 16
 
15.8%
3 3
 
3.0%
0 3
 
3.0%
6 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%
4 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
25.0%
S 1
25.0%
R 1
25.0%
M 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 21
65.6%
, 8
 
25.0%
/ 3
 
9.4%
Math Symbol
ValueCountFrequency (%)
> 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
1287
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
r 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7359
83.0%
Common 1500
 
16.9%
Latin 5
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 308
 
4.2%
교 269
 
3.7%
사 269
 
3.7%
인 267
 
3.6%
정 262
 
3.6%
무 229
 
3.1%
업 222
 
3.0%
소 210
 
2.9%
취 208
 
2.8%
불 193
 
2.6%
Other values (274) 4922
66.9%
Common
ValueCountFrequency (%)
1287
85.8%
1 47
 
3.1%
( 36
 
2.4%
) 36
 
2.4%
9 28
 
1.9%
. 21
 
1.4%
2 16
 
1.1%
, 8
 
0.5%
- 4
 
0.3%
3 3
 
0.2%
Other values (9) 14
 
0.9%
Latin
ValueCountFrequency (%)
r 1
20.0%
E 1
20.0%
S 1
20.0%
R 1
20.0%
M 1
20.0%
Han
ValueCountFrequency (%)
中 1
50.0%
喪 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7359
83.0%
ASCII 1505
 
17.0%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1287
85.5%
1 47
 
3.1%
( 36
 
2.4%
) 36
 
2.4%
9 28
 
1.9%
. 21
 
1.4%
2 16
 
1.1%
, 8
 
0.5%
- 4
 
0.3%
3 3
 
0.2%
Other values (14) 19
 
1.3%
Hangul
ValueCountFrequency (%)
로 308
 
4.2%
교 269
 
3.7%
사 269
 
3.7%
인 267
 
3.6%
정 262
 
3.6%
무 229
 
3.1%
업 222
 
3.0%
소 210
 
2.9%
취 208
 
2.8%
불 193
 
2.6%
Other values (274) 4922
66.9%
CJK
ValueCountFrequency (%)
中 1
50.0%
喪 1
50.0%

적용여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing20
Missing (%)2.1%
Memory size2.0 KiB
True
947 
(Missing)
 
20
ValueCountFrequency (%)
True 947
97.9%
(Missing) 20
 
2.1%
2024-04-17T18:20:55.796746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전표번호
Text

MISSING 

Distinct945
Distinct (%)100.0%
Missing22
Missing (%)2.3%
Memory size7.7 KiB
2024-04-17T18:20:55.954194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters12285
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique945 ?
Unique (%)100.0%

Sample

1st rowF201204100006
2nd rowF201204100003
3rd rowF201204100005
4th rowF201204100004
5th rowF201204190007
ValueCountFrequency (%)
f201205170001 1
 
0.1%
f201805160001 1
 
0.1%
f201806110003 1
 
0.1%
f201804230001 1
 
0.1%
f201804230002 1
 
0.1%
f201804300002 1
 
0.1%
f201804300003 1
 
0.1%
f201805030001 1
 
0.1%
f201805090001 1
 
0.1%
f201805090002 1
 
0.1%
Other values (935) 935
98.9%
2024-04-17T18:20:56.209988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4813
39.2%
1 1975
16.1%
2 1942
15.8%
F 945
 
7.7%
5 466
 
3.8%
3 428
 
3.5%
6 414
 
3.4%
4 372
 
3.0%
8 342
 
2.8%
7 329
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11340
92.3%
Uppercase Letter 945
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4813
42.4%
1 1975
17.4%
2 1942
17.1%
5 466
 
4.1%
3 428
 
3.8%
6 414
 
3.7%
4 372
 
3.3%
8 342
 
3.0%
7 329
 
2.9%
9 259
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
F 945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11340
92.3%
Latin 945
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4813
42.4%
1 1975
17.4%
2 1942
17.1%
5 466
 
4.1%
3 428
 
3.8%
6 414
 
3.7%
4 372
 
3.3%
8 342
 
3.0%
7 329
 
2.9%
9 259
 
2.3%
Latin
ValueCountFrequency (%)
F 945
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4813
39.2%
1 1975
16.1%
2 1942
15.8%
F 945
 
7.7%
5 466
 
3.8%
3 428
 
3.5%
6 414
 
3.4%
4 372
 
3.0%
8 342
 
2.8%
7 329
 
2.7%

등록자
Text

Distinct876
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-04-17T18:20:56.484728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.7880041
Min length4

Characters and Unicode

Total characters7531
Distinct characters39
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

Unique796 ?
Unique (%)82.3%

Sample

1st rowejlee
2nd rowsjee22
3rd rowrlarse
4th rowskhumhchung
5th rowgkswjddms
ValueCountFrequency (%)
kbae0e 4
 
0.4%
seoilkim 3
 
0.3%
kimjh 3
 
0.3%
bluellroca 3
 
0.3%
tm0880 3
 
0.3%
soojung126 3
 
0.3%
kmj486 3
 
0.3%
sam12250 3
 
0.3%
pknush 3
 
0.3%
d154250 3
 
0.3%
Other values (866) 936
96.8%
2024-04-17T18:20:56.854699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 444
 
5.9%
s 428
 
5.7%
o 403
 
5.4%
a 397
 
5.3%
e 386
 
5.1%
0 377
 
5.0%
1 343
 
4.6%
i 324
 
4.3%
2 307
 
4.1%
k 299
 
4.0%
Other values (29) 3823
50.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5436
72.2%
Decimal Number 2088
 
27.7%
Uppercase Letter 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 444
 
8.2%
s 428
 
7.9%
o 403
 
7.4%
a 397
 
7.3%
e 386
 
7.1%
i 324
 
6.0%
k 299
 
5.5%
h 287
 
5.3%
j 270
 
5.0%
u 237
 
4.4%
Other values (16) 1961
36.1%
Decimal Number
ValueCountFrequency (%)
0 377
18.1%
1 343
16.4%
2 307
14.7%
7 189
9.1%
9 177
8.5%
5 163
7.8%
3 157
7.5%
4 128
 
6.1%
8 124
 
5.9%
6 123
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
D 3
42.9%
M 2
28.6%
K 2
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 5443
72.3%
Common 2088
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 444
 
8.2%
s 428
 
7.9%
o 403
 
7.4%
a 397
 
7.3%
e 386
 
7.1%
i 324
 
6.0%
k 299
 
5.5%
h 287
 
5.3%
j 270
 
5.0%
u 237
 
4.4%
Other values (19) 1968
36.2%
Common
ValueCountFrequency (%)
0 377
18.1%
1 343
16.4%
2 307
14.7%
7 189
9.1%
9 177
8.5%
5 163
7.8%
3 157
7.5%
4 128
 
6.1%
8 124
 
5.9%
6 123
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 444
 
5.9%
s 428
 
5.7%
o 403
 
5.4%
a 397
 
5.3%
e 386
 
5.1%
0 377
 
5.0%
1 343
 
4.6%
i 324
 
4.3%
2 307
 
4.1%
k 299
 
4.0%
Other values (29) 3823
50.8%

등록일자
Date

Distinct543
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
Minimum2012-02-17 00:00:00
Maximum2020-12-03 00:00:00
2024-04-17T18:20:56.970426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:20:57.078942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
mhhwang
197 
dhlee1
144 
kimjh
143 
thkim
127 
seojk
119 
Other values (8)
237 

Length

Max length8
Median length5
Mean length5.7466391
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
mhhwang 197
20.4%
dhlee1 144
14.9%
kimjh 143
14.8%
thkim 127
13.1%
seojk 119
12.3%
kimhj 63
 
6.5%
mjpark01 61
 
6.3%
bmlee 37
 
3.8%
jmpark 23
 
2.4%
<NA> 22
 
2.3%
Other values (3) 31
 
3.2%

Length

2024-04-17T18:20:57.203277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mhhwang 197
20.4%
dhlee1 144
14.9%
kimjh 143
14.8%
thkim 127
13.1%
seojk 119
12.3%
kimhj 63
 
6.5%
mjpark01 61
 
6.3%
bmlee 37
 
3.8%
jmpark 23
 
2.4%
na 22
 
2.3%
Other values (3) 31
 
3.2%

수정일자
Date

MISSING 

Distinct347
Distinct (%)36.7%
Missing22
Missing (%)2.3%
Memory size7.7 KiB
Minimum2012-04-10 00:00:00
Maximum2020-12-07 00:00:00
2024-04-17T18:20:57.311729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:20:57.415251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

통장사본
Text

MISSING 

Distinct609
Distinct (%)100.0%
Missing358
Missing (%)37.0%
Memory size7.7 KiB
2024-04-17T18:20:57.607620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length36
Mean length16.753695
Min length6

Characters and Unicode

Total characters10203
Distinct characters284
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique609 ?
Unique (%)100.0%

Sample

1st row통장사본(황병숙)(1).pdf
2nd rowUntitled_20150605_044925(1).pdf
3rd row통장사본.jpg
4th row김진휘통장사본.pdf
5th row김해덕(통장사본).pdf
ValueCountFrequency (%)
통장사본.pdf 44
 
4.9%
통장 26
 
2.9%
사본.pdf 21
 
2.3%
통장사본.jpg 11
 
1.2%
간접비 9
 
1.0%
교비 9
 
1.0%
7
 
0.8%
통장사본(1).pdf 6
 
0.7%
계좌.pdf 6
 
0.7%
산학협력단 6
 
0.7%
Other values (661) 762
84.0%
2024-04-17T18:20:57.977948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 621
 
6.1%
p 584
 
5.7%
d 507
 
5.0%
f 501
 
4.9%
1 491
 
4.8%
0 469
 
4.6%
장 393
 
3.9%
통 392
 
3.8%
사 388
 
3.8%
본 369
 
3.6%
Other values (274) 5488
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4008
39.3%
Decimal Number 2140
21.0%
Lowercase Letter 1988
19.5%
Other Punctuation 623
 
6.1%
Close Punctuation 332
 
3.3%
Open Punctuation 332
 
3.3%
Space Separator 298
 
2.9%
Uppercase Letter 214
 
2.1%
Connector Punctuation 154
 
1.5%
Dash Punctuation 114
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 393
 
9.8%
통 392
 
9.8%
사 388
 
9.7%
본 369
 
9.2%
교 217
 
5.4%
학 213
 
5.3%
대 204
 
5.1%
비 109
 
2.7%
계 90
 
2.2%
좌 71
 
1.8%
Other values (213) 1562
39.0%
Lowercase Letter
ValueCountFrequency (%)
p 584
29.4%
d 507
25.5%
f 501
25.2%
g 93
 
4.7%
j 81
 
4.1%
a 27
 
1.4%
i 24
 
1.2%
n 22
 
1.1%
o 22
 
1.1%
e 22
 
1.1%
Other values (13) 105
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
S 41
19.2%
C 21
9.8%
P 20
9.3%
D 17
7.9%
F 14
 
6.5%
B 14
 
6.5%
K 12
 
5.6%
M 12
 
5.6%
T 11
 
5.1%
A 11
 
5.1%
Other values (9) 41
19.2%
Decimal Number
ValueCountFrequency (%)
1 491
22.9%
0 469
21.9%
2 272
12.7%
4 170
 
7.9%
3 158
 
7.4%
5 147
 
6.9%
8 132
 
6.2%
6 116
 
5.4%
7 99
 
4.6%
9 86
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 621
99.7%
, 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 318
95.8%
] 14
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 318
95.8%
[ 14
 
4.2%
Space Separator
ValueCountFrequency (%)
298
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4008
39.3%
Common 3993
39.1%
Latin 2202
21.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 393
 
9.8%
통 392
 
9.8%
사 388
 
9.7%
본 369
 
9.2%
교 217
 
5.4%
학 213
 
5.3%
대 204
 
5.1%
비 109
 
2.7%
계 90
 
2.2%
좌 71
 
1.8%
Other values (213) 1562
39.0%
Latin
ValueCountFrequency (%)
p 584
26.5%
d 507
23.0%
f 501
22.8%
g 93
 
4.2%
j 81
 
3.7%
S 41
 
1.9%
a 27
 
1.2%
i 24
 
1.1%
n 22
 
1.0%
o 22
 
1.0%
Other values (32) 300
13.6%
Common
ValueCountFrequency (%)
. 621
15.6%
1 491
12.3%
0 469
11.7%
) 318
8.0%
( 318
8.0%
298
7.5%
2 272
 
6.8%
4 170
 
4.3%
3 158
 
4.0%
_ 154
 
3.9%
Other values (9) 724
18.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6195
60.7%
Hangul 4008
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 621
 
10.0%
p 584
 
9.4%
d 507
 
8.2%
f 501
 
8.1%
1 491
 
7.9%
0 469
 
7.6%
) 318
 
5.1%
( 318
 
5.1%
298
 
4.8%
2 272
 
4.4%
Other values (51) 1816
29.3%
Hangul
ValueCountFrequency (%)
장 393
 
9.8%
통 392
 
9.8%
사 388
 
9.7%
본 369
 
9.2%
교 217
 
5.4%
학 213
 
5.3%
대 204
 
5.1%
비 109
 
2.7%
계 90
 
2.2%
좌 71
 
1.8%
Other values (213) 1562
39.0%

환불개인통장 반환사유
Text

MISSING 

Distinct42
Distinct (%)80.8%
Missing915
Missing (%)94.6%
Memory size7.7 KiB
2024-04-17T18:20:58.238837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length36
Mean length21.403846
Min length2

Characters and Unicode

Total characters1113
Distinct characters166
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)61.5%

Sample

1st row 2일간 1인실 이용에 따른 개인부담,개인통장 우리은행입니다.
2nd row 2일간 1인실 이용에 따른 개인부담,개인통장 우리은행입니다.
3rd row사비부담이므로
4th row입금착오
5th row회계 처리 문제
ValueCountFrequency (%)
1인실 16
 
6.2%
개인 9
 
3.5%
따른 7
 
2.7%
입금 7
 
2.7%
개인이 6
 
2.3%
개인통장으로 4
 
1.6%
개인부담 4
 
1.6%
후 4
 
1.6%
반환 4
 
1.6%
환불 4
 
1.6%
Other values (138) 191
74.6%
2024-04-17T18:20:58.630322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
18.7%
인 73
 
6.6%
개 42
 
3.8%
금 35
 
3.1%
실 27
 
2.4%
입 27
 
2.4%
1 22
 
2.0%
로 21
 
1.9%
비 18
 
1.6%
에 18
 
1.6%
Other values (156) 622
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 832
74.8%
Space Separator 208
 
18.7%
Decimal Number 33
 
3.0%
Other Punctuation 14
 
1.3%
Lowercase Letter 14
 
1.3%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Uppercase Letter 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 73
 
8.8%
개 42
 
5.0%
금 35
 
4.2%
실 27
 
3.2%
입 27
 
3.2%
로 21
 
2.5%
비 18
 
2.2%
에 18
 
2.2%
부 18
 
2.2%
으 17
 
2.0%
Other values (132) 536
64.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
14.3%
n 2
14.3%
k 2
14.3%
c 2
14.3%
o 1
7.1%
w 1
7.1%
y 1
7.1%
g 1
7.1%
r 1
7.1%
s 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 22
66.7%
2 7
 
21.2%
3 2
 
6.1%
7 1
 
3.0%
6 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 10
71.4%
, 3
 
21.4%
@ 1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
E 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
208
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 832
74.8%
Common 263
 
23.6%
Latin 18
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 73
 
8.8%
개 42
 
5.0%
금 35
 
4.2%
실 27
 
3.2%
입 27
 
3.2%
로 21
 
2.5%
비 18
 
2.2%
에 18
 
2.2%
부 18
 
2.2%
으 17
 
2.0%
Other values (132) 536
64.4%
Latin
ValueCountFrequency (%)
a 2
11.1%
n 2
11.1%
k 2
11.1%
c 2
11.1%
T 2
11.1%
E 1
 
5.6%
o 1
 
5.6%
w 1
 
5.6%
y 1
 
5.6%
g 1
 
5.6%
Other values (3) 3
16.7%
Common
ValueCountFrequency (%)
208
79.1%
1 22
 
8.4%
. 10
 
3.8%
2 7
 
2.7%
( 4
 
1.5%
) 4
 
1.5%
, 3
 
1.1%
3 2
 
0.8%
7 1
 
0.4%
@ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 832
74.8%
ASCII 281
 
25.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
74.0%
1 22
 
7.8%
. 10
 
3.6%
2 7
 
2.5%
( 4
 
1.4%
) 4
 
1.4%
, 3
 
1.1%
a 2
 
0.7%
n 2
 
0.7%
k 2
 
0.7%
Other values (14) 17
 
6.0%
Hangul
ValueCountFrequency (%)
인 73
 
8.8%
개 42
 
5.0%
금 35
 
4.2%
실 27
 
3.2%
입 27
 
3.2%
로 21
 
2.5%
비 18
 
2.2%
에 18
 
2.2%
부 18
 
2.2%
으 17
 
2.0%
Other values (132) 536
64.4%

Unnamed: 16
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
<NA>
957 
회계팀 제출(6.20)
 
4
9.3 회계팀 제출
 
3
9.4 회계팀 제출
 
2
(7.12) 회계팀 제출
 
1

Length

Max length13
Median length4
Mean length4.073423
Min length4

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> 957
99.0%
회계팀 제출(6.20) 4
 
0.4%
9.3 회계팀 제출 3
 
0.3%
9.4 회계팀 제출 2
 
0.2%
(7.12) 회계팀 제출 1
 
0.1%

Length

2024-04-17T18:20:59.001946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:20:59.086468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 957
97.4%
회계팀 10
 
1.0%
제출 6
 
0.6%
제출(6.20 4
 
0.4%
9.3 3
 
0.3%
9.4 2
 
0.2%
7.12 1
 
0.1%

Interactions

2024-04-17T18:20:51.825730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:20:51.695548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:20:51.892830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:20:51.759097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T18:20:59.152642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연수번호순번수납은행코드환불요청금액수정자환불개인통장 반환사유Unnamed: 16
연수번호1.0000.0750.1220.3510.974NaNNaN
순번0.0751.0000.0000.2170.0860.0000.000
수납은행코드0.1220.0001.0000.1300.1700.9480.837
환불요청금액0.3510.2170.1301.0000.5560.8930.621
수정자0.9740.0860.1700.5561.0001.000NaN
환불개인통장 반환사유NaN0.0000.9480.8931.0001.0000.000
Unnamed: 16NaN0.0000.8370.621NaN0.0001.000
2024-04-17T18:20:59.269145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수정자순번연수번호Unnamed: 16
수정자1.0000.0660.8571.000
순번0.0661.0000.0480.000
연수번호0.8570.0481.0001.000
Unnamed: 161.0000.0001.0001.000
2024-04-17T18:20:59.362345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수납은행코드환불요청금액연수번호순번수정자Unnamed: 16
수납은행코드1.000-0.0300.0910.0000.0720.445
환불요청금액-0.0301.0000.3500.2160.2730.186
연수번호0.0910.3501.0000.0480.8571.000
순번0.0000.2160.0481.0000.0660.000
수정자0.0720.2730.8570.0661.0001.000
Unnamed: 160.4450.1861.0000.0001.0001.000

Missing values

2024-04-17T18:20:52.019703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:20:52.224613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-04-17T18:20:52.346400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연수번호사용자아이디순번수납은행코드환불요청금액환불담당자소속환불담당자직위환불사유적용여부전표번호등록자등록일자수정자수정일자통장사본환불개인통장 반환사유Unnamed: 16
02010000000000000ejlee1450000재단주임연수취소<NA><NA>ejlee2012-02-17<NA><NA><NA><NA><NA>
12010000000000000sjee22111270000산학협력단법인직원감사로인한 연수취소<NA><NA>sjee222012-03-12<NA><NA><NA><NA><NA>
22010000000000000rlarse111380000산학협력단법인직원내부사정<NA><NA>rlarse2012-03-12<NA><NA><NA><NA><NA>
32010000000000000skhumhchung15380000연구처주임회계감사로 인한 참가불가YF201204100006skhumhchung2012-03-27kimjh2012-04-10<NA><NA><NA>
42010000000000000gkswjddms14380000총무처직원학교결산업무YF201204100003gkswjddms2012-03-29kimjh2012-04-10<NA><NA><NA>
52010000000000000legalcjy120380000삼육대학교산학협력단재무팀장회계법인감사YF201204100005legalcjy2012-03-30kimjh2012-04-10<NA><NA><NA>
62010000000000000soojung126120380000서울시립대학교산학협력단담당학교 일정 참석으로 인한 불참YF201204100004soojung1262012-04-03kimjh2012-04-10<NA><NA><NA>
72010000000000000jyb580214380000사무처팀장학교일정YF201204190007jyb58022012-04-04kimjh2012-04-19<NA><NA><NA>
82010000000000000iwilla181380000산학협력단 경영총괄팀계장학교업무 발생으로 교육참석 불가YF201204190006iwilla2012-04-13kimjh2012-04-19<NA><NA><NA>
92010000000000000dong20067049132380000신라대 산단 행정팀팀장개인 사정YF201204190005dong200670492012-04-19kimjh2012-04-19<NA><NA><NA>
연수번호사용자아이디순번수납은행코드환불요청금액환불담당자소속환불담당자직위환불사유적용여부전표번호등록자등록일자수정자수정일자통장사본환불개인통장 반환사유Unnamed: 16
9572020000000000000heesoo30271200차의과학대학교주임연수 취소YF202011300009heesoo30272020-11-30seojk2020-11-30차의과학대학교 통장사본(등록금).pdf<NA><NA>
9582020000000000000kakimjk1200서울여자대학교부장교육취소YF202011300010kakimjk2020-11-30seojk2020-11-30서울여자대학교.jpg<NA><NA>
9592020000000000000catcats79137270000경리팀주임과정 취소YF202011300011catcats792020-11-30seojk2020-11-30환불 통장사본(우석대학교).pdf<NA><NA>
9602020000000000000ojh5142188270000백석대학교 대학평가원사원코로나 19로 연수 취소YF202011300012ojh51422020-11-30seojk2020-11-30학교 통장 사본.pdf<NA><NA>
9612020000000000000no1393140기획조정처팀장코로나로 인해 연수취소YF202012010002no13932020-11-30seojk2020-12-0101. 국민은행 - 교비(등록금회계)(4).pdf<NA><NA>
9622020000000000000caleb2119111270000학교법인삼육학원차장코로나 2단계 거리두기 로인한 연수취소YF202012010003caleb21192020-11-30seojk2020-12-01농협통장사본.pdf<NA><NA>
9632020000000000000drmlee140기획행정처직원교육취소YF202012010004drmlee2020-12-01seojk2020-12-01국민은행 (경상비).pdf<NA><NA>
9642020000000000000jaehong2139270000재무팀주임교육취소YF202012010005jaehong22020-12-01seojk2020-12-01창신대학교 사업자등록증.pdf<NA><NA>
9652020000000000000ggolade139270000울산대학교 총무팀과장코로나 19로 인한 취소YF202012020001ggolade2020-12-02seojk2020-12-02울산대학교 대표계좌(등록금).pdf<NA><NA>
9662020000000000000iossoi120270000사무처직원코로나19로 연수 취소됨YF202012070001iossoi2020-12-03seojk2020-12-07대학원 통장사본.pdf<NA><NA>