Overview

Dataset statistics

Number of variables49
Number of observations7023
Missing cells100571
Missing cells (%)29.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory412.0 B

Variable types

Numeric12
Categorical19
DateTime3
Boolean5
Text10

Dataset

DescriptionRA시험접수(교육SEQ값, 교육그룹이름, 교육CODE, 시행년도)
Author한국의료기기안전정보원
URLhttps://www.data.go.kr/data/15066856/fileData.do

Alerts

RECEPTION_AGREE has constant value ""Constant
POLICIES_AGREE has constant value ""Constant
ER_REC_TYPE is highly imbalanced (83.4%)Imbalance
ER_STATUS is highly imbalanced (68.5%)Imbalance
ER_EUNGSILYO is highly imbalanced (60.7%)Imbalance
HADICAP_YN is highly imbalanced (89.7%)Imbalance
CARR_EVIDENCE_PATH is highly imbalanced (79.5%)Imbalance
ER_RECEIPT_NO has 698 (9.9%) missing valuesMissing
ER_PASS_YN has 979 (13.9%) missing valuesMissing
ER_CERT_YN has 2434 (34.7%) missing valuesMissing
ER_CERT_NO has 6055 (86.2%) missing valuesMissing
ER_EXAM_SUB1 has 1369 (19.5%) missing valuesMissing
ER_EXAM_SUB2 has 1841 (26.2%) missing valuesMissing
ER_EXAM_SUB3 has 1355 (19.3%) missing valuesMissing
ER_EXAM_SUB4 has 1844 (26.3%) missing valuesMissing
ER_EXAM_SUB5 has 1843 (26.2%) missing valuesMissing
HADICAP_YN has 3696 (52.6%) missing valuesMissing
HADICAP_FNAME has 7013 (99.9%) missing valuesMissing
LAST_EDU_NM has 6195 (88.2%) missing valuesMissing
LAST_EDU_DEPARTMENT has 6296 (89.6%) missing valuesMissing
GRADUATION_DATE has 6195 (88.2%) missing valuesMissing
EDU_EVIDENCE_FNAME has 6195 (88.2%) missing valuesMissing
TOTAL_CAREER has 6799 (96.8%) missing valuesMissing
CARR_EVIDENCE_FNAME has 6798 (96.8%) missing valuesMissing
EXAM_QUALIFICATION has 3729 (53.1%) missing valuesMissing
RECEPTION_AGREE has 5660 (80.6%) missing valuesMissing
POLICIES_AGREE has 5660 (80.6%) missing valuesMissing
RECEPTION_AGREE_DATE has 5660 (80.6%) missing valuesMissing
POLICIES_AGREE_DATE has 5660 (80.6%) missing valuesMissing
RA_CERT_NO has 5374 (76.5%) missing valuesMissing
ER_EXAM_AVG has 1223 (17.4%) missing valuesMissing
RECEIPT_SEQ has unique valuesUnique
ER_EXAM_SUB1 has 770 (11.0%) zerosZeros
ER_EXAM_SUB2 has 980 (14.0%) zerosZeros
ER_EXAM_SUB3 has 724 (10.3%) zerosZeros
ER_EXAM_SUB4 has 1008 (14.4%) zerosZeros
ER_EXAM_SUB5 has 1007 (14.3%) zerosZeros
EXAM_QUALIFICATION has 852 (12.1%) zerosZeros
ER_EXAM_AVG has 680 (9.7%) zerosZeros

Reproduction

Analysis started2023-12-12 10:12:46.500392
Analysis finished2023-12-12 10:12:48.533705
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

RECEIPT_SEQ
Real number (ℝ)

UNIQUE 

Distinct7023
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3825.3869
Minimum7
Maximum7480
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:48.646482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile494.1
Q12069.5
median3825
Q35580.5
95-th percentile7128.9
Maximum7480
Range7473
Interquartile range (IQR)3511

Descriptive statistics

Standard deviation2098.6838
Coefficient of variation (CV)0.54862002
Kurtosis-1.1341022
Mean3825.3869
Median Absolute Deviation (MAD)1756
Skewness-0.0069054774
Sum26865692
Variance4404473.8
MonotonicityNot monotonic
2023-12-12T19:12:48.853312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112 1
 
< 0.1%
5667 1
 
< 0.1%
5483 1
 
< 0.1%
5476 1
 
< 0.1%
5463 1
 
< 0.1%
5459 1
 
< 0.1%
5457 1
 
< 0.1%
5456 1
 
< 0.1%
5454 1
 
< 0.1%
5449 1
 
< 0.1%
Other values (7013) 7013
99.9%
ValueCountFrequency (%)
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
7480 1
< 0.1%
7479 1
< 0.1%
7478 1
< 0.1%
7477 1
< 0.1%
7476 1
< 0.1%
7475 1
< 0.1%
7474 1
< 0.1%
7473 1
< 0.1%
7472 1
< 0.1%
7471 1
< 0.1%

GROUP_NAME
Categorical

Distinct40
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
2019년 의료기기 RA 전문가 2급
1351 
2020년 의료기기 RA 전문가 2급
982 
2017년 의료기기 RA 전문가 2급
848 
2016년 의료기기 RA 전문가 2급
814 
2018년 의료기기 RA 전문가 2급
704 
Other values (35)
2324 

Length

Max length24
Median length20
Mean length19.858892
Min length7

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2014년 의료기기 RA 전문가 2급
2nd row2014년 의료기기 RA 전문가 2급
3rd row2014년 의료기기 RA 전문가 2급
4th row2014년 의료기기 RA 전문가 2급
5th row2014년 의료기기 RA 전문가 2급

Common Values

ValueCountFrequency (%)
2019년 의료기기 RA 전문가 2급 1351
19.2%
2020년 의료기기 RA 전문가 2급 982
14.0%
2017년 의료기기 RA 전문가 2급 848
12.1%
2016년 의료기기 RA 전문가 2급 814
11.6%
2018년 의료기기 RA 전문가 2급 704
10.0%
2019년 의료기기 RA 전문가 2급(완화) 552
7.9%
2015년 의료기기 RA 전문가 2급 507
 
7.2%
2014년 의료기기 RA 전문가 2급 461
 
6.6%
2020년 의료기기 RA 전문가 2급(완화) 293
 
4.2%
[인허가] 필기 84
 
1.2%
Other values (30) 427
 
6.1%

Length

2023-12-12T19:12:49.078301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ra 6512
19.4%
전문가 6512
19.4%
의료기기 6512
19.4%
2급 5667
16.9%
2019년 1903
 
5.7%
2020년 1275
 
3.8%
2017년 848
 
2.5%
2급(완화 845
 
2.5%
2016년 814
 
2.4%
2018년 704
 
2.1%
Other values (19) 1989
 
5.9%

GROUP_CODE
Categorical

Distinct48
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
1902
1351 
2002
982 
1702
848 
1602
814 
1802
704 
Other values (43)
2324 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row1402
2nd row1402
3rd row1402
4th row1402
5th row1402

Common Values

ValueCountFrequency (%)
1902 1351
19.2%
2002 982
14.0%
1702 848
12.1%
1602 814
11.6%
1802 704
10.0%
1903 552
7.9%
1502 507
 
7.2%
1402 461
 
6.6%
2003 293
 
4.2%
2011 33
 
0.5%
Other values (38) 478
 
6.8%

Length

2023-12-12T19:12:49.254194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1902 1351
19.2%
2002 982
14.0%
1702 848
12.1%
1602 814
11.6%
1802 704
10.0%
1903 552
7.9%
1502 507
 
7.2%
1402 461
 
6.6%
2003 293
 
4.2%
2011 33
 
0.5%
Other values (37) 478
 
6.8%

ES_YEAR
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.7689
Minimum2014
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:49.376306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32019
95-th percentile2020
Maximum2020
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8564984
Coefficient of variation (CV)0.00092007482
Kurtosis-0.90594301
Mean2017.7689
Median Absolute Deviation (MAD)1
Skewness-0.52556346
Sum14170791
Variance3.4465862
MonotonicityNot monotonic
2023-12-12T19:12:49.498580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2019 1989
28.3%
2020 1360
19.4%
2017 953
13.6%
2016 893
12.7%
2018 784
 
11.2%
2015 583
 
8.3%
2014 461
 
6.6%
ValueCountFrequency (%)
2014 461
 
6.6%
2015 583
 
8.3%
2016 893
12.7%
2017 953
13.6%
2018 784
 
11.2%
2019 1989
28.3%
2020 1360
19.4%
ValueCountFrequency (%)
2020 1360
19.4%
2019 1989
28.3%
2018 784
 
11.2%
2017 953
13.6%
2016 893
12.7%
2015 583
 
8.3%
2014 461
 
6.6%

ES_ORDER
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
1
3867 
2
2406 
3
743 
10
 
7

Length

Max length2
Median length1
Mean length1.0009967
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 3867
55.1%
2 2406
34.3%
3 743
 
10.6%
10 7
 
0.1%

Length

2023-12-12T19:12:49.663321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:49.801378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3867
55.1%
2 2406
34.3%
3 743
 
10.6%
10 7
 
0.1%

ER_RECEIPT_NO
Real number (ℝ)

MISSING 

Distinct6325
Distinct (%)100.0%
Missing698
Missing (%)9.9%
Infinite0
Infinite (%)0.0%
Mean3164.5037
Minimum1
Maximum6329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:49.963316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile317.2
Q11582
median3164
Q34748
95-th percentile6012.8
Maximum6329
Range6328
Interquartile range (IQR)3166

Descriptive statistics

Standard deviation1827.4747
Coefficient of variation (CV)0.57749171
Kurtosis-1.2002187
Mean3164.5037
Median Absolute Deviation (MAD)1583
Skewness0.00064118748
Sum20015486
Variance3339663.6
MonotonicityNot monotonic
2023-12-12T19:12:50.150015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4801 1
 
< 0.1%
4626 1
 
< 0.1%
4616 1
 
< 0.1%
4611 1
 
< 0.1%
4746 1
 
< 0.1%
4440 1
 
< 0.1%
4441 1
 
< 0.1%
4439 1
 
< 0.1%
4436 1
 
< 0.1%
4535 1
 
< 0.1%
Other values (6315) 6315
89.9%
(Missing) 698
 
9.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
6329 1
< 0.1%
6328 1
< 0.1%
6327 1
< 0.1%
6326 1
< 0.1%
6325 1
< 0.1%
6324 1
< 0.1%
6323 1
< 0.1%
6322 1
< 0.1%
6321 1
< 0.1%
6320 1
< 0.1%
Distinct222
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
Minimum2014-11-03 00:00:00
Maximum2020-08-10 00:00:00
2023-12-12T19:12:50.339060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:50.535533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3021
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
Minimum1952-01-10 00:00:00
Maximum2020-12-03 00:00:00
2023-12-12T19:12:50.728139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:12:50.882251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

ER_USER_GENDER
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
4231 
2792 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
4231
60.2%
2792
39.8%

Length

2023-12-12T19:12:51.029172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:51.150014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4231
60.2%
2792
39.8%

ER_REC_TYPE
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
우편발송
6851 
방문수령
 
172

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row방문수령
2nd row우편발송
3rd row우편발송
4th row우편발송
5th row우편발송

Common Values

ValueCountFrequency (%)
우편발송 6851
97.6%
방문수령 172
 
2.4%

Length

2023-12-12T19:12:51.279413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:51.445516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우편발송 6851
97.6%
방문수령 172
 
2.4%

ER_STATUS
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
접수완료
6111 
접수취소
 
467
접수미승인
 
361
접수승인
 
83
미응시
 
1

Length

Max length5
Median length4
Mean length4.0512601
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
접수완료 6111
87.0%
접수취소 467
 
6.6%
접수미승인 361
 
5.1%
접수승인 83
 
1.2%
미응시 1
 
< 0.1%

Length

2023-12-12T19:12:51.964965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:52.112513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
접수완료 6111
87.0%
접수취소 467
 
6.6%
접수미승인 361
 
5.1%
접수승인 83
 
1.2%
미응시 1
 
< 0.1%

ER_PASS_YN
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing979
Missing (%)13.9%
Memory size13.8 KiB
False
4279 
True
1765 
(Missing)
979 
ValueCountFrequency (%)
False 4279
60.9%
True 1765
25.1%
(Missing) 979
 
13.9%
2023-12-12T19:12:52.288191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

ER_CERT_YN
Boolean

MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2434
Missing (%)34.7%
Memory size13.8 KiB
False
2484 
True
2105 
(Missing)
2434 
ValueCountFrequency (%)
False 2484
35.4%
True 2105
30.0%
(Missing) 2434
34.7%
2023-12-12T19:12:52.395486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

ER_CERT_NO
Real number (ℝ)

MISSING 

Distinct968
Distinct (%)100.0%
Missing6055
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean485.14566
Minimum1
Maximum969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:52.547019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile49.35
Q1242.75
median485.5
Q3727.25
95-th percentile920.65
Maximum969
Range968
Interquartile range (IQR)484.5

Descriptive statistics

Standard deviation279.97843
Coefficient of variation (CV)0.57710179
Kurtosis-1.2009836
Mean485.14566
Median Absolute Deviation (MAD)242.5
Skewness-0.0014316475
Sum469621
Variance78387.92
MonotonicityNot monotonic
2023-12-12T19:12:52.720114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
640 1
 
< 0.1%
544 1
 
< 0.1%
560 1
 
< 0.1%
618 1
 
< 0.1%
623 1
 
< 0.1%
622 1
 
< 0.1%
621 1
 
< 0.1%
631 1
 
< 0.1%
742 1
 
< 0.1%
748 1
 
< 0.1%
Other values (958) 958
 
13.6%
(Missing) 6055
86.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
969 1
< 0.1%
968 1
< 0.1%
967 1
< 0.1%
966 1
< 0.1%
965 1
< 0.1%
964 1
< 0.1%
963 1
< 0.1%
962 1
< 0.1%
961 1
< 0.1%
960 1
< 0.1%

ER_CERT_TYPE
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
카드,상장
3356 
상장
2295 
<NA>
1099 
카드
 
273

Length

Max length5
Median length4
Mean length3.7465471
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
카드,상장 3356
47.8%
상장 2295
32.7%
<NA> 1099
 
15.6%
카드 273
 
3.9%

Length

2023-12-12T19:12:52.882070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:53.018643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
카드,상장 3356
47.8%
상장 2295
32.7%
na 1099
 
15.6%
카드 273
 
3.9%

ER_EUNGSILYO
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
50000
4885 
무료
1231 
10000
845 
100000
 
35
1000
 
22
Other values (4)
 
5

Length

Max length9
Median length5
Mean length4.4748683
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
50000 4885
69.6%
무료 1231
 
17.5%
10000 845
 
12.0%
100000 35
 
0.5%
1000 22
 
0.3%
1 2
 
< 0.1%
<NA> 1
 
< 0.1%
10 1
 
< 0.1%
300000000 1
 
< 0.1%

Length

2023-12-12T19:12:53.213101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:53.377708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50000 4885
69.6%
무료 1231
 
17.5%
10000 845
 
12.0%
100000 35
 
0.5%
1000 22
 
0.3%
1 2
 
< 0.1%
na 1
 
< 0.1%
10 1
 
< 0.1%
300000000 1
 
< 0.1%
Distinct4284
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
2023-12-12T19:12:53.782062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters49161
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2600 ?
Unique (%)37.0%

Sample

1st row38:00.4
2nd row33:23.9
3rd row34:07.0
4th row33:36.2
5th row34:36.5
ValueCountFrequency (%)
51:48.0 7
 
0.1%
42:32.0 7
 
0.1%
41:53.0 7
 
0.1%
12:40.0 6
 
0.1%
20:09.0 6
 
0.1%
33:14.0 6
 
0.1%
46:40.0 6
 
0.1%
01:05.0 6
 
0.1%
35:08.0 6
 
0.1%
25:41.0 6
 
0.1%
Other values (4274) 6960
99.1%
2023-12-12T19:12:54.299591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9308
18.9%
: 7023
14.3%
. 7023
14.3%
4 4042
8.2%
2 3953
8.0%
1 3883
7.9%
3 3867
7.9%
5 3798
7.7%
8 1607
 
3.3%
6 1569
 
3.2%
Other values (2) 3088
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35115
71.4%
Other Punctuation 14046
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9308
26.5%
4 4042
11.5%
2 3953
11.3%
1 3883
11.1%
3 3867
11.0%
5 3798
10.8%
8 1607
 
4.6%
6 1569
 
4.5%
7 1565
 
4.5%
9 1523
 
4.3%
Other Punctuation
ValueCountFrequency (%)
: 7023
50.0%
. 7023
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9308
18.9%
: 7023
14.3%
. 7023
14.3%
4 4042
8.2%
2 3953
8.0%
1 3883
7.9%
3 3867
7.9%
5 3798
7.7%
8 1607
 
3.3%
6 1569
 
3.2%
Other values (2) 3088
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9308
18.9%
: 7023
14.3%
. 7023
14.3%
4 4042
8.2%
2 3953
8.0%
1 3883
7.9%
3 3867
7.9%
5 3798
7.7%
8 1607
 
3.3%
6 1569
 
3.2%
Other values (2) 3088
 
6.3%
Distinct3141
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
2023-12-12T19:12:54.675974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters49161
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1653 ?
Unique (%)23.5%

Sample

1st row44:39.0
2nd row44:39.0
3rd row52:05.2
4th row33:26.0
5th row35:07.0
ValueCountFrequency (%)
28:20.0 17
 
0.2%
30:50.0 15
 
0.2%
26:38.0 15
 
0.2%
30:47.0 13
 
0.2%
55:49.0 13
 
0.2%
30:37.0 13
 
0.2%
35:47.0 13
 
0.2%
27:48.0 12
 
0.2%
26:22.0 12
 
0.2%
56:45.0 12
 
0.2%
Other values (3131) 6888
98.1%
2023-12-12T19:12:55.244314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9350
19.0%
: 7023
14.3%
. 7023
14.3%
2 4332
8.8%
5 4068
8.3%
3 3885
7.9%
4 3661
 
7.4%
1 3650
 
7.4%
6 1619
 
3.3%
7 1597
 
3.2%
Other values (2) 2953
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35115
71.4%
Other Punctuation 14046
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9350
26.6%
2 4332
12.3%
5 4068
11.6%
3 3885
11.1%
4 3661
 
10.4%
1 3650
 
10.4%
6 1619
 
4.6%
7 1597
 
4.5%
8 1482
 
4.2%
9 1471
 
4.2%
Other Punctuation
ValueCountFrequency (%)
: 7023
50.0%
. 7023
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9350
19.0%
: 7023
14.3%
. 7023
14.3%
2 4332
8.8%
5 4068
8.3%
3 3885
7.9%
4 3661
 
7.4%
1 3650
 
7.4%
6 1619
 
3.3%
7 1597
 
3.2%
Other values (2) 2953
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9350
19.0%
: 7023
14.3%
. 7023
14.3%
2 4332
8.8%
5 4068
8.3%
3 3885
7.9%
4 3661
 
7.4%
1 3650
 
7.4%
6 1619
 
3.3%
7 1597
 
3.2%
Other values (2) 2953
 
6.0%

ER_EXAM_SUB_CNT
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
5
2689 
<NA>
2682 
0
884 
2
763 
1
 
5

Length

Max length4
Median length1
Mean length2.1456642
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
5 2689
38.3%
<NA> 2682
38.2%
0 884
 
12.6%
2 763
 
10.9%
1 5
 
0.1%

Length

2023-12-12T19:12:55.423959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:55.573802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 2689
38.3%
na 2682
38.2%
0 884
 
12.6%
2 763
 
10.9%
1 5
 
0.1%

ER_EXAM_SUB1
Real number (ℝ)

MISSING  ZEROS 

Distinct69
Distinct (%)1.2%
Missing1369
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean50.554652
Minimum0
Maximum100
Zeros770
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:55.753279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q140
median55
Q369
95-th percentile84
Maximum100
Range100
Interquartile range (IQR)29

Descriptive statistics

Standard deviation24.773785
Coefficient of variation (CV)0.49003967
Kurtosis-0.083941964
Mean50.554652
Median Absolute Deviation (MAD)15
Skewness-0.82648
Sum285836
Variance613.74042
MonotonicityNot monotonic
2023-12-12T19:12:55.925465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 770
 
11.0%
60 419
 
6.0%
55 400
 
5.7%
65 385
 
5.5%
50 365
 
5.2%
70 343
 
4.9%
45 320
 
4.6%
75 275
 
3.9%
40 245
 
3.5%
80 206
 
2.9%
Other values (59) 1926
27.4%
(Missing) 1369
19.5%
ValueCountFrequency (%)
0 770
11.0%
5 2
 
< 0.1%
10 3
 
< 0.1%
15 13
 
0.2%
20 31
 
0.4%
22 3
 
< 0.1%
25 69
 
1.0%
27 2
 
< 0.1%
29 8
 
0.1%
30 111
 
1.6%
ValueCountFrequency (%)
100 4
 
0.1%
95 29
 
0.4%
94 1
 
< 0.1%
93 1
 
< 0.1%
90 91
1.3%
89 4
 
0.1%
88 7
 
0.1%
86 2
 
< 0.1%
85 141
2.0%
84 5
 
0.1%

ER_EXAM_SUB2
Real number (ℝ)

MISSING  ZEROS 

Distinct64
Distinct (%)1.2%
Missing1841
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean42.858935
Minimum0
Maximum100
Zeros980
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:56.087574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q135
median50
Q360
95-th percentile75
Maximum100
Range100
Interquartile range (IQR)25

Descriptive statistics

Standard deviation24.256136
Coefficient of variation (CV)0.56595285
Kurtosis-0.58044589
Mean42.858935
Median Absolute Deviation (MAD)13
Skewness-0.63635898
Sum222095
Variance588.36014
MonotonicityNot monotonic
2023-12-12T19:12:56.280084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 980
14.0%
55 460
 
6.5%
50 441
 
6.3%
45 402
 
5.7%
60 363
 
5.2%
40 335
 
4.8%
65 295
 
4.2%
70 242
 
3.4%
35 230
 
3.3%
75 159
 
2.3%
Other values (54) 1275
18.2%
(Missing) 1841
26.2%
ValueCountFrequency (%)
0 980
14.0%
5 2
 
< 0.1%
10 1
 
< 0.1%
15 7
 
0.1%
17 2
 
< 0.1%
20 29
 
0.4%
22 9
 
0.1%
25 77
 
1.1%
26 1
 
< 0.1%
27 18
 
0.3%
ValueCountFrequency (%)
100 1
 
< 0.1%
95 2
 
< 0.1%
90 15
 
0.2%
86 2
 
< 0.1%
85 53
0.8%
81 6
 
0.1%
80 106
1.5%
78 6
 
0.1%
77 1
 
< 0.1%
76 17
 
0.2%

ER_EXAM_SUB3
Real number (ℝ)

MISSING  ZEROS 

Distinct73
Distinct (%)1.3%
Missing1355
Missing (%)19.3%
Infinite0
Infinite (%)0.0%
Mean51.044989
Minimum0
Maximum100
Zeros724
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:56.462895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q140
median55
Q368
95-th percentile80
Maximum100
Range100
Interquartile range (IQR)28

Descriptive statistics

Standard deviation24.12357
Coefficient of variation (CV)0.47259428
Kurtosis0.10502248
Mean51.044989
Median Absolute Deviation (MAD)13
Skewness-0.90058311
Sum289323
Variance581.94663
MonotonicityNot monotonic
2023-12-12T19:12:56.616454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 724
 
10.3%
60 465
 
6.6%
55 462
 
6.6%
65 416
 
5.9%
70 362
 
5.2%
50 347
 
4.9%
45 317
 
4.5%
75 274
 
3.9%
40 254
 
3.6%
80 193
 
2.7%
Other values (63) 1854
26.4%
(Missing) 1355
19.3%
ValueCountFrequency (%)
0 724
10.3%
5 1
 
< 0.1%
10 4
 
0.1%
15 16
 
0.2%
20 22
 
0.3%
22 5
 
0.1%
24 1
 
< 0.1%
25 66
 
0.9%
27 8
 
0.1%
29 4
 
0.1%
ValueCountFrequency (%)
100 8
 
0.1%
95 23
 
0.3%
93 1
 
< 0.1%
91 3
 
< 0.1%
90 64
0.9%
89 1
 
< 0.1%
88 8
 
0.1%
87 1
 
< 0.1%
86 10
 
0.1%
85 113
1.6%

ER_EXAM_SUB4
Real number (ℝ)

MISSING  ZEROS 

Distinct80
Distinct (%)1.5%
Missing1844
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean42.616142
Minimum0
Maximum100
Zeros1008
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:56.790510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130
median48
Q360
95-th percentile75
Maximum100
Range100
Interquartile range (IQR)30

Descriptive statistics

Standard deviation24.82093
Coefficient of variation (CV)0.58243025
Kurtosis-0.67892139
Mean42.616142
Median Absolute Deviation (MAD)13
Skewness-0.5533494
Sum220709
Variance616.07858
MonotonicityNot monotonic
2023-12-12T19:12:56.947386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1008
14.4%
55 357
 
5.1%
50 357
 
5.1%
60 314
 
4.5%
45 289
 
4.1%
65 264
 
3.8%
40 234
 
3.3%
70 228
 
3.2%
35 184
 
2.6%
75 159
 
2.3%
Other values (70) 1785
25.4%
(Missing) 1844
26.3%
ValueCountFrequency (%)
0 1008
14.4%
5 1
 
< 0.1%
7 1
 
< 0.1%
10 4
 
0.1%
15 10
 
0.1%
17 2
 
< 0.1%
18 2
 
< 0.1%
20 29
 
0.4%
22 13
 
0.2%
23 3
 
< 0.1%
ValueCountFrequency (%)
100 1
 
< 0.1%
96 1
 
< 0.1%
95 8
 
0.1%
91 4
 
0.1%
90 26
0.4%
89 1
 
< 0.1%
88 2
 
< 0.1%
87 2
 
< 0.1%
86 4
 
0.1%
85 47
0.7%

ER_EXAM_SUB5
Real number (ℝ)

MISSING  ZEROS 

Distinct72
Distinct (%)1.4%
Missing1843
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean40.61834
Minimum0
Maximum99
Zeros1007
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:12:57.100637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q127
median45
Q359
95-th percentile72.05
Maximum99
Range99
Interquartile range (IQR)32

Descriptive statistics

Standard deviation23.908384
Coefficient of variation (CV)0.58861057
Kurtosis-0.7720806
Mean40.61834
Median Absolute Deviation (MAD)15
Skewness-0.54902512
Sum210403
Variance571.61082
MonotonicityNot monotonic
2023-12-12T19:12:57.282117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1007
14.3%
55 395
 
5.6%
50 382
 
5.4%
60 352
 
5.0%
45 337
 
4.8%
65 312
 
4.4%
40 256
 
3.6%
70 195
 
2.8%
35 171
 
2.4%
75 134
 
1.9%
Other values (62) 1639
23.3%
(Missing) 1843
26.2%
ValueCountFrequency (%)
0 1007
14.3%
5 2
 
< 0.1%
7 2
 
< 0.1%
10 9
 
0.1%
12 7
 
0.1%
14 2
 
< 0.1%
15 27
 
0.4%
17 15
 
0.2%
19 9
 
0.1%
20 43
 
0.6%
ValueCountFrequency (%)
99 1
 
< 0.1%
90 11
 
0.2%
87 1
 
< 0.1%
86 2
 
< 0.1%
85 24
 
0.3%
82 1
 
< 0.1%
80 66
0.9%
79 1
 
< 0.1%
78 3
 
< 0.1%
77 4
 
0.1%

ER_EXAM_SUB6
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
5350 
0
1673 

Length

Max length4
Median length4
Mean length3.2853481
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5350
76.2%
0 1673
 
23.8%

Length

2023-12-12T19:12:57.441012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:57.556966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5350
76.2%
0 1673
 
23.8%

ER_EXAM_SUB7
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
5349 
0
1674 

Length

Max length4
Median length4
Mean length3.284921
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5349
76.2%
0 1674
 
23.8%

Length

2023-12-12T19:12:57.693547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:57.829011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5349
76.2%
0 1674
 
23.8%

ER_EXAM_SUB8
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
5349 
0
1674 

Length

Max length4
Median length4
Mean length3.284921
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5349
76.2%
0 1674
 
23.8%

Length

2023-12-12T19:12:58.040308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:58.152296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5349
76.2%
0 1674
 
23.8%

ER_EXAM_SUB9
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
5349 
0
1674 

Length

Max length4
Median length4
Mean length3.284921
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5349
76.2%
0 1674
 
23.8%

Length

2023-12-12T19:12:58.286222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:58.400026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5349
76.2%
0 1674
 
23.8%

ER_EXAM_SUB10
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
5349 
0
1674 

Length

Max length4
Median length4
Mean length3.284921
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5349
76.2%
0 1674
 
23.8%

Length

2023-12-12T19:12:58.515184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:58.637371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5349
76.2%
0 1674
 
23.8%

LAST_EDU
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
3731 
대졸
2169 
석/박사
759 
고졸
 
238
초대졸
 
126

Length

Max length5
Median length4
Mean length3.4046704
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3731
53.1%
대졸 2169
30.9%
석/박사 759
 
10.8%
고졸 238
 
3.4%
초대졸 126
 
1.8%

Length

2023-12-12T19:12:58.783636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:58.907352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3731
53.1%
대졸 2169
30.9%
석/박사 759
 
10.8%
고졸 238
 
3.4%
초대졸 126
 
1.8%

HADICAP_YN
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing3696
Missing (%)52.6%
Memory size13.8 KiB
False
3282 
True
 
45
(Missing)
3696 
ValueCountFrequency (%)
False 3282
46.7%
True 45
 
0.6%
(Missing) 3696
52.6%
2023-12-12T19:12:59.021869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

HADICAP_FNAME
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing7013
Missing (%)99.9%
Memory size55.0 KiB
2023-12-12T19:12:59.187149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length11.6
Min length7

Characters and Unicode

Total characters116
Distinct characters44
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

Unique10 ?
Unique (%)100.0%

Sample

1st row홈페이지 - 복사본.zip
2nd row장애증빙자료.zip
3rd rowDesktop.zip
4th row장애인증명서1.pdf
5th row장애증빙자료1.zip
ValueCountFrequency (%)
홈페이지 1
8.3%
1
8.3%
복사본.zip 1
8.3%
장애증빙자료.zip 1
8.3%
desktop.zip 1
8.3%
장애인증명서1.pdf 1
8.3%
장애증빙자료1.zip 1
8.3%
소견서.zip 1
8.3%
20190329_임신확인서.zip 1
8.3%
002.zip 1
8.3%
Other values (2) 2
16.7%
2023-12-12T19:12:59.634129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
p 11
 
9.5%
0 10
 
8.6%
. 10
 
8.6%
z 9
 
7.8%
i 9
 
7.8%
2 6
 
5.2%
1 5
 
4.3%
9 4
 
3.4%
3
 
2.6%
3
 
2.6%
Other values (34) 46
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
31.9%
Lowercase Letter 36
31.0%
Decimal Number 27
23.3%
Other Punctuation 10
 
8.6%
Space Separator 2
 
1.7%
Connector Punctuation 2
 
1.7%
Uppercase Letter 1
 
0.9%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (13) 13
35.1%
Lowercase Letter
ValueCountFrequency (%)
p 11
30.6%
z 9
25.0%
i 9
25.0%
f 1
 
2.8%
k 1
 
2.8%
d 1
 
2.8%
o 1
 
2.8%
t 1
 
2.8%
s 1
 
2.8%
e 1
 
2.8%
Decimal Number
ValueCountFrequency (%)
0 10
37.0%
2 6
22.2%
1 5
18.5%
9 4
 
14.8%
3 1
 
3.7%
5 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
36.2%
Latin 37
31.9%
Hangul 37
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (13) 13
35.1%
Latin
ValueCountFrequency (%)
p 11
29.7%
z 9
24.3%
i 9
24.3%
f 1
 
2.7%
k 1
 
2.7%
d 1
 
2.7%
o 1
 
2.7%
t 1
 
2.7%
s 1
 
2.7%
e 1
 
2.7%
Common
ValueCountFrequency (%)
0 10
23.8%
. 10
23.8%
2 6
14.3%
1 5
11.9%
9 4
 
9.5%
2
 
4.8%
_ 2
 
4.8%
3 1
 
2.4%
- 1
 
2.4%
5 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
68.1%
Hangul 37
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 11
13.9%
0 10
12.7%
. 10
12.7%
z 9
11.4%
i 9
11.4%
2 6
7.6%
1 5
6.3%
9 4
 
5.1%
2
 
2.5%
_ 2
 
2.5%
Other values (11) 11
13.9%
Hangul
ValueCountFrequency (%)
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (13) 13
35.1%

HADICAP_PATH
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
3729 
/files/receipt/
3294 

Length

Max length15
Median length4
Mean length9.1593336
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3729
53.1%
/files/receipt/ 3294
46.9%

Length

2023-12-12T19:12:59.781124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:12:59.915305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3729
53.1%
files/receipt 3294
46.9%

LAST_EDU_NM
Text

MISSING 

Distinct193
Distinct (%)23.3%
Missing6195
Missing (%)88.2%
Memory size55.0 KiB
2023-12-12T19:13:00.249253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length5
Mean length5.7330918
Min length2

Characters and Unicode

Total characters4747
Distinct characters186
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

Unique85 ?
Unique (%)10.3%

Sample

1st row을지대학교
2nd row인천대학교
3rd row전남대학교
4th row서울시립대학교
5th row전북대학교
ValueCountFrequency (%)
건국대학교 38
 
4.4%
인제대학교 34
 
3.9%
연세대학교 34
 
3.9%
전북대학교 30
 
3.5%
을지대학교 27
 
3.1%
건양대학교 26
 
3.0%
부경대학교 24
 
2.8%
가천대학교 21
 
2.4%
단국대학교 18
 
2.1%
금오공과대학교 17
 
2.0%
Other values (189) 594
68.8%
2023-12-12T19:13:00.808995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
865
18.2%
829
17.5%
794
16.7%
95
 
2.0%
75
 
1.6%
71
 
1.5%
69
 
1.5%
62
 
1.3%
59
 
1.2%
55
 
1.2%
Other values (176) 1773
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4546
95.8%
Lowercase Letter 112
 
2.4%
Space Separator 43
 
0.9%
Uppercase Letter 37
 
0.8%
Decimal Number 4
 
0.1%
Other Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
865
19.0%
829
18.2%
794
17.5%
95
 
2.1%
75
 
1.6%
71
 
1.6%
69
 
1.5%
62
 
1.4%
59
 
1.3%
55
 
1.2%
Other values (136) 1572
34.6%
Lowercase Letter
ValueCountFrequency (%)
i 18
16.1%
n 16
14.3%
e 12
10.7%
s 10
8.9%
o 10
8.9%
t 9
8.0%
y 7
 
6.2%
r 7
 
6.2%
v 5
 
4.5%
a 5
 
4.5%
Other values (6) 13
11.6%
Uppercase Letter
ValueCountFrequency (%)
U 7
18.9%
S 4
10.8%
M 4
10.8%
I 3
8.1%
R 3
8.1%
T 3
8.1%
N 2
 
5.4%
E 2
 
5.4%
O 2
 
5.4%
G 1
 
2.7%
Other values (6) 6
16.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
4 1
25.0%
2 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
43
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4546
95.8%
Latin 149
 
3.1%
Common 52
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
865
19.0%
829
18.2%
794
17.5%
95
 
2.1%
75
 
1.6%
71
 
1.6%
69
 
1.5%
62
 
1.4%
59
 
1.3%
55
 
1.2%
Other values (136) 1572
34.6%
Latin
ValueCountFrequency (%)
i 18
 
12.1%
n 16
 
10.7%
e 12
 
8.1%
s 10
 
6.7%
o 10
 
6.7%
t 9
 
6.0%
y 7
 
4.7%
r 7
 
4.7%
U 7
 
4.7%
v 5
 
3.4%
Other values (22) 48
32.2%
Common
ValueCountFrequency (%)
43
82.7%
. 2
 
3.8%
1 2
 
3.8%
4 1
 
1.9%
2 1
 
1.9%
+ 1
 
1.9%
, 1
 
1.9%
- 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4546
95.8%
ASCII 201
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
865
19.0%
829
18.2%
794
17.5%
95
 
2.1%
75
 
1.6%
71
 
1.6%
69
 
1.5%
62
 
1.4%
59
 
1.3%
55
 
1.2%
Other values (136) 1572
34.6%
ASCII
ValueCountFrequency (%)
43
21.4%
i 18
 
9.0%
n 16
 
8.0%
e 12
 
6.0%
s 10
 
5.0%
o 10
 
5.0%
t 9
 
4.5%
y 7
 
3.5%
r 7
 
3.5%
U 7
 
3.5%
Other values (30) 62
30.8%

LAST_EDU_DEPARTMENT
Text

MISSING 

Distinct195
Distinct (%)26.8%
Missing6296
Missing (%)89.6%
Memory size55.0 KiB
2023-12-12T19:13:01.131114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length11.13205
Min length5

Characters and Unicode

Total characters8093
Distinct characters130
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)13.5%

Sample

1st row방사선학(과·전공)
2nd row생명과학전공
3rd row의공학(과·전공·부)
4th row생명과학(과·전공·부·계열·군)
5th row바이오메디컬공학부
ValueCountFrequency (%)
의공학(과·전공·부 83
 
11.4%
의용공학(과·전공 37
 
5.1%
화학(과·부 29
 
4.0%
생명공학(과·전공·부·공학전공 24
 
3.3%
바이오메디컬공학부 23
 
3.2%
의료공학과 22
 
3.0%
의료공학(과·부·전공 22
 
3.0%
생명과학(과·전공·부·계열·군 20
 
2.7%
의학공학부 12
 
1.6%
화학·화학공학과군 11
 
1.5%
Other values (187) 446
61.2%
2023-12-12T19:13:02.005490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
· 1023
12.6%
1011
12.5%
868
10.7%
741
 
9.2%
578
 
7.1%
( 524
 
6.5%
) 523
 
6.5%
396
 
4.9%
246
 
3.0%
190
 
2.3%
Other values (120) 1993
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5987
74.0%
Other Punctuation 1035
 
12.8%
Open Punctuation 524
 
6.5%
Close Punctuation 523
 
6.5%
Uppercase Letter 22
 
0.3%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1011
16.9%
868
14.5%
741
12.4%
578
 
9.7%
396
 
6.6%
246
 
4.1%
190
 
3.2%
148
 
2.5%
113
 
1.9%
109
 
1.8%
Other values (112) 1587
26.5%
Other Punctuation
ValueCountFrequency (%)
· 1023
98.8%
. 10
 
1.0%
, 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
I 11
50.0%
T 11
50.0%
Open Punctuation
ValueCountFrequency (%)
( 524
100.0%
Close Punctuation
ValueCountFrequency (%)
) 523
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5987
74.0%
Common 2084
 
25.8%
Latin 22
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1011
16.9%
868
14.5%
741
12.4%
578
 
9.7%
396
 
6.6%
246
 
4.1%
190
 
3.2%
148
 
2.5%
113
 
1.9%
109
 
1.8%
Other values (112) 1587
26.5%
Common
ValueCountFrequency (%)
· 1023
49.1%
( 524
25.1%
) 523
25.1%
. 10
 
0.5%
, 2
 
0.1%
2
 
0.1%
Latin
ValueCountFrequency (%)
I 11
50.0%
T 11
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5987
74.0%
ASCII 1083
 
13.4%
None 1023
 
12.6%

Most frequent character per block

None
ValueCountFrequency (%)
· 1023
100.0%
Hangul
ValueCountFrequency (%)
1011
16.9%
868
14.5%
741
12.4%
578
 
9.7%
396
 
6.6%
246
 
4.1%
190
 
3.2%
148
 
2.5%
113
 
1.9%
109
 
1.8%
Other values (112) 1587
26.5%
ASCII
ValueCountFrequency (%)
( 524
48.4%
) 523
48.3%
I 11
 
1.0%
T 11
 
1.0%
. 10
 
0.9%
, 2
 
0.2%
2
 
0.2%

GRADUATION_DATE
Date

MISSING 

Distinct305
Distinct (%)36.8%
Missing6195
Missing (%)88.2%
Memory size55.0 KiB
Minimum1973-01-02 00:00:00
Maximum2021-02-25 00:00:00
2023-12-12T19:13:02.227845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:13:02.419045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

EDU_EVIDENCE_FNAME
Text

MISSING 

Distinct828
Distinct (%)100.0%
Missing6195
Missing (%)88.2%
Memory size55.0 KiB
2023-12-12T19:13:02.782515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length14.082126
Min length6

Characters and Unicode

Total characters11660
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

Unique828 ?
Unique (%)100.0%

Sample

1st row졸업증명서38.zip
2nd row김수현 졸업증빙.zip
3rd row학위증명서_양윤라.zip
4th row졸업증명서78.zip
5th row전북대학교_졸업예정증명서1.zip
ValueCountFrequency (%)
졸업증명서.zip 35
 
3.3%
졸업증명서 25
 
2.4%
졸업 9
 
0.9%
증명서.zip 8
 
0.8%
8
 
0.8%
학부 6
 
0.6%
6
 
0.6%
2).zip 6
 
0.6%
졸업증명서1.zip 5
 
0.5%
학사 5
 
0.5%
Other values (879) 938
89.2%
2023-12-12T19:13:03.368683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 860
 
7.4%
. 852
 
7.3%
p 848
 
7.3%
z 821
 
7.0%
699
 
6.0%
662
 
5.7%
650
 
5.6%
602
 
5.2%
600
 
5.1%
_ 309
 
2.7%
Other values (274) 4757
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5575
47.8%
Lowercase Letter 2968
25.5%
Decimal Number 1325
 
11.4%
Other Punctuation 863
 
7.4%
Connector Punctuation 309
 
2.7%
Space Separator 223
 
1.9%
Uppercase Letter 142
 
1.2%
Dash Punctuation 86
 
0.7%
Close Punctuation 85
 
0.7%
Open Punctuation 84
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
699
12.5%
662
 
11.9%
650
 
11.7%
602
 
10.8%
600
 
10.8%
256
 
4.6%
140
 
2.5%
102
 
1.8%
91
 
1.6%
74
 
1.3%
Other values (207) 1699
30.5%
Lowercase Letter
ValueCountFrequency (%)
i 860
29.0%
p 848
28.6%
z 821
27.7%
a 67
 
2.3%
e 50
 
1.7%
t 43
 
1.4%
r 33
 
1.1%
n 32
 
1.1%
o 31
 
1.0%
d 25
 
0.8%
Other values (14) 158
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 13
 
9.2%
D 11
 
7.7%
R 10
 
7.0%
P 10
 
7.0%
I 10
 
7.0%
K 9
 
6.3%
S 9
 
6.3%
G 9
 
6.3%
A 8
 
5.6%
E 7
 
4.9%
Other values (13) 46
32.4%
Decimal Number
ValueCountFrequency (%)
1 302
22.8%
2 236
17.8%
0 215
16.2%
3 103
 
7.8%
4 97
 
7.3%
5 94
 
7.1%
9 86
 
6.5%
6 71
 
5.4%
8 66
 
5.0%
7 55
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 852
98.7%
, 9
 
1.0%
! 2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 81
95.3%
] 4
 
4.7%
Open Punctuation
ValueCountFrequency (%)
( 80
95.2%
[ 4
 
4.8%
Connector Punctuation
ValueCountFrequency (%)
_ 309
100.0%
Space Separator
ValueCountFrequency (%)
223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5575
47.8%
Latin 3110
26.7%
Common 2975
25.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
699
12.5%
662
 
11.9%
650
 
11.7%
602
 
10.8%
600
 
10.8%
256
 
4.6%
140
 
2.5%
102
 
1.8%
91
 
1.6%
74
 
1.3%
Other values (207) 1699
30.5%
Latin
ValueCountFrequency (%)
i 860
27.7%
p 848
27.3%
z 821
26.4%
a 67
 
2.2%
e 50
 
1.6%
t 43
 
1.4%
r 33
 
1.1%
n 32
 
1.0%
o 31
 
1.0%
d 25
 
0.8%
Other values (37) 300
 
9.6%
Common
ValueCountFrequency (%)
. 852
28.6%
_ 309
 
10.4%
1 302
 
10.2%
2 236
 
7.9%
223
 
7.5%
0 215
 
7.2%
3 103
 
3.5%
4 97
 
3.3%
5 94
 
3.2%
- 86
 
2.9%
Other values (10) 458
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6085
52.2%
Hangul 5575
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 860
14.1%
. 852
14.0%
p 848
13.9%
z 821
13.5%
_ 309
 
5.1%
1 302
 
5.0%
2 236
 
3.9%
223
 
3.7%
0 215
 
3.5%
3 103
 
1.7%
Other values (57) 1316
21.6%
Hangul
ValueCountFrequency (%)
699
12.5%
662
 
11.9%
650
 
11.7%
602
 
10.8%
600
 
10.8%
256
 
4.6%
140
 
2.5%
102
 
1.8%
91
 
1.6%
74
 
1.3%
Other values (207) 1699
30.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
6195 
/files/receipt/
828 

Length

Max length15
Median length4
Mean length5.2968817
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6195
88.2%
/files/receipt/ 828
 
11.8%

Length

2023-12-12T19:13:03.571536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:13:03.700922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6195
88.2%
files/receipt 828
 
11.8%

TOTAL_CAREER
Text

MISSING 

Distinct106
Distinct (%)47.3%
Missing6799
Missing (%)96.8%
Memory size55.0 KiB
2023-12-12T19:13:03.889374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2142857
Min length3

Characters and Unicode

Total characters1392
Distinct characters14
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

Unique51 ?
Unique (%)22.8%

Sample

1st row3년 7개월
2nd row2년 0개월
3rd row7년 8개월
4th row2년 9개월
5th row3년 5개월
ValueCountFrequency (%)
1년 40
 
8.9%
3년 34
 
7.6%
2년 32
 
7.2%
5년 28
 
6.3%
0개월 27
 
6.0%
4년 24
 
5.4%
9개월 23
 
5.1%
2개월 23
 
5.1%
1개월 21
 
4.7%
4개월 19
 
4.3%
Other values (19) 176
39.4%
2023-12-12T19:13:04.300141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
224
16.1%
224
16.1%
223
16.0%
223
16.0%
1 131
9.4%
2 59
 
4.2%
3 51
 
3.7%
0 49
 
3.5%
4 45
 
3.2%
5 43
 
3.1%
Other values (4) 120
8.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 671
48.2%
Decimal Number 498
35.8%
Space Separator 223
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 131
26.3%
2 59
11.8%
3 51
 
10.2%
0 49
 
9.8%
4 45
 
9.0%
5 43
 
8.6%
7 34
 
6.8%
6 30
 
6.0%
9 28
 
5.6%
8 28
 
5.6%
Other Letter
ValueCountFrequency (%)
224
33.4%
224
33.4%
223
33.2%
Space Separator
ValueCountFrequency (%)
223
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 721
51.8%
Hangul 671
48.2%

Most frequent character per script

Common
ValueCountFrequency (%)
223
30.9%
1 131
18.2%
2 59
 
8.2%
3 51
 
7.1%
0 49
 
6.8%
4 45
 
6.2%
5 43
 
6.0%
7 34
 
4.7%
6 30
 
4.2%
9 28
 
3.9%
Hangul
ValueCountFrequency (%)
224
33.4%
224
33.4%
223
33.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 721
51.8%
Hangul 671
48.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
224
33.4%
224
33.4%
223
33.2%
ASCII
ValueCountFrequency (%)
223
30.9%
1 131
18.2%
2 59
 
8.2%
3 51
 
7.1%
0 49
 
6.8%
4 45
 
6.2%
5 43
 
6.0%
7 34
 
4.7%
6 30
 
4.2%
9 28
 
3.9%

CARR_EVIDENCE_FNAME
Text

MISSING 

Distinct225
Distinct (%)100.0%
Missing6798
Missing (%)96.8%
Memory size55.0 KiB
2023-12-12T19:13:04.681811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length31
Mean length13.902222
Min length6

Characters and Unicode

Total characters3128
Distinct characters230
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

Unique225 ?
Unique (%)100.0%

Sample

1st row경력증명서4.zip
2nd row전효진_재직증명_건강보험.zip
3rd row경력증명13.zip
4th row경력정보 증명서_김명선.zip
5th row경력증빙자료14.zip
ValueCountFrequency (%)
경력증명서.zip 7
 
2.3%
재직증명서.zip 6
 
2.0%
경력 5
 
1.6%
김상욱 3
 
1.0%
3
 
1.0%
경력증명서 3
 
1.0%
재직증명서 3
 
1.0%
3
 
1.0%
주)파마리서치프로덕트 2
 
0.7%
ra자격증 2
 
0.7%
Other values (261) 267
87.8%
2023-12-12T19:13:05.220232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
p 230
 
7.4%
. 229
 
7.3%
i 223
 
7.1%
z 221
 
7.1%
172
 
5.5%
154
 
4.9%
147
 
4.7%
96
 
3.1%
93
 
3.0%
1 88
 
2.8%
Other values (220) 1475
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1450
46.4%
Lowercase Letter 753
24.1%
Decimal Number 423
 
13.5%
Other Punctuation 234
 
7.5%
Space Separator 79
 
2.5%
Connector Punctuation 73
 
2.3%
Uppercase Letter 56
 
1.8%
Close Punctuation 22
 
0.7%
Open Punctuation 22
 
0.7%
Dash Punctuation 16
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
172
 
11.9%
154
 
10.6%
147
 
10.1%
96
 
6.6%
93
 
6.4%
65
 
4.5%
64
 
4.4%
36
 
2.5%
26
 
1.8%
22
 
1.5%
Other values (162) 575
39.7%
Lowercase Letter
ValueCountFrequency (%)
p 230
30.5%
i 223
29.6%
z 221
29.3%
e 11
 
1.5%
o 10
 
1.3%
a 8
 
1.1%
k 8
 
1.1%
s 6
 
0.8%
t 6
 
0.8%
n 5
 
0.7%
Other values (10) 25
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
A 9
16.1%
D 7
12.5%
R 7
12.5%
C 5
8.9%
S 4
 
7.1%
N 3
 
5.4%
P 3
 
5.4%
I 3
 
5.4%
K 3
 
5.4%
Z 2
 
3.6%
Other values (9) 10
17.9%
Decimal Number
ValueCountFrequency (%)
1 88
20.8%
2 74
17.5%
0 52
12.3%
3 46
10.9%
4 42
9.9%
9 32
 
7.6%
5 28
 
6.6%
7 23
 
5.4%
6 19
 
4.5%
8 19
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 229
97.9%
, 5
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 21
95.5%
] 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 21
95.5%
[ 1
 
4.5%
Space Separator
ValueCountFrequency (%)
79
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1450
46.4%
Common 869
27.8%
Latin 809
25.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
172
 
11.9%
154
 
10.6%
147
 
10.1%
96
 
6.6%
93
 
6.4%
65
 
4.5%
64
 
4.4%
36
 
2.5%
26
 
1.8%
22
 
1.5%
Other values (162) 575
39.7%
Latin
ValueCountFrequency (%)
p 230
28.4%
i 223
27.6%
z 221
27.3%
e 11
 
1.4%
o 10
 
1.2%
A 9
 
1.1%
a 8
 
1.0%
k 8
 
1.0%
D 7
 
0.9%
R 7
 
0.9%
Other values (29) 75
 
9.3%
Common
ValueCountFrequency (%)
. 229
26.4%
1 88
 
10.1%
79
 
9.1%
2 74
 
8.5%
_ 73
 
8.4%
0 52
 
6.0%
3 46
 
5.3%
4 42
 
4.8%
9 32
 
3.7%
5 28
 
3.2%
Other values (9) 126
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1678
53.6%
Hangul 1450
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 230
13.7%
. 229
13.6%
i 223
13.3%
z 221
13.2%
1 88
 
5.2%
79
 
4.7%
2 74
 
4.4%
_ 73
 
4.4%
0 52
 
3.1%
3 46
 
2.7%
Other values (48) 363
21.6%
Hangul
ValueCountFrequency (%)
172
 
11.9%
154
 
10.6%
147
 
10.1%
96
 
6.6%
93
 
6.4%
65
 
4.5%
64
 
4.4%
36
 
2.5%
26
 
1.8%
22
 
1.5%
Other values (162) 575
39.7%

CARR_EVIDENCE_PATH
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
6798 
/files/receipt/
 
225

Length

Max length15
Median length4
Mean length4.3524135
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6798
96.8%
/files/receipt/ 225
 
3.2%

Length

2023-12-12T19:13:05.397141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:13:05.518005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6798
96.8%
files/receipt 225
 
3.2%

EXAM_QUALIFICATION
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.2%
Missing3729
Missing (%)53.1%
Infinite0
Infinite (%)0.0%
Mean1.1208257
Minimum0
Maximum6
Zeros852
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:13:05.618725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.0140093
Coefficient of variation (CV)0.90469841
Kurtosis5.7206925
Mean1.1208257
Median Absolute Deviation (MAD)1
Skewness1.7378084
Sum3692
Variance1.0282148
MonotonicityNot monotonic
2023-12-12T19:13:05.772267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1568
22.3%
0 852
 
12.1%
2 653
 
9.3%
3 159
 
2.3%
6 42
 
0.6%
4 11
 
0.2%
5 9
 
0.1%
(Missing) 3729
53.1%
ValueCountFrequency (%)
0 852
12.1%
1 1568
22.3%
2 653
9.3%
3 159
 
2.3%
4 11
 
0.2%
5 9
 
0.1%
6 42
 
0.6%
ValueCountFrequency (%)
6 42
 
0.6%
5 9
 
0.1%
4 11
 
0.2%
3 159
 
2.3%
2 653
9.3%
1 1568
22.3%
0 852
12.1%

CHK_GRADE
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.0 KiB
<NA>
3729 
2
3202 
1
 
92

Length

Max length4
Median length4
Mean length2.592909
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 (%)
<NA> 3729
53.1%
2 3202
45.6%
1 92
 
1.3%

Length

2023-12-12T19:13:05.924795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:13:06.053249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3729
53.1%
2 3202
45.6%
1 92
 
1.3%

RECEPTION_AGREE
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing5660
Missing (%)80.6%
Memory size13.8 KiB
True
1363 
(Missing)
5660 
ValueCountFrequency (%)
True 1363
 
19.4%
(Missing) 5660
80.6%
2023-12-12T19:13:06.140276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

POLICIES_AGREE
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing5660
Missing (%)80.6%
Memory size13.8 KiB
True
1363 
(Missing)
5660 
ValueCountFrequency (%)
True 1363
 
19.4%
(Missing) 5660
80.6%
2023-12-12T19:13:06.218185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

RECEPTION_AGREE_DATE
Text

MISSING 

Distinct1129
Distinct (%)82.8%
Missing5660
Missing (%)80.6%
Memory size55.0 KiB
2023-12-12T19:13:06.559401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters9541
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique925 ?
Unique (%)67.9%

Sample

1st row39:34.0
2nd row44:08.0
3rd row29:05.0
4th row27:51.0
5th row30:38.0
ValueCountFrequency (%)
48:37.0 5
 
0.4%
54:14.0 4
 
0.3%
03:59.0 4
 
0.3%
04:31.0 4
 
0.3%
47:44.0 3
 
0.2%
28:08.0 3
 
0.2%
11:40.0 3
 
0.2%
13:10.0 3
 
0.2%
44:47.0 3
 
0.2%
19:54.0 3
 
0.2%
Other values (1119) 1328
97.4%
2023-12-12T19:13:07.085155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6815
71.4%
Other Punctuation 2726
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2154
31.6%
1 764
 
11.2%
4 755
 
11.1%
2 708
 
10.4%
3 699
 
10.3%
5 642
 
9.4%
7 294
 
4.3%
9 273
 
4.0%
6 268
 
3.9%
8 258
 
3.8%
Other Punctuation
ValueCountFrequency (%)
: 1363
50.0%
. 1363
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9541
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

POLICIES_AGREE_DATE
Text

MISSING 

Distinct1129
Distinct (%)82.8%
Missing5660
Missing (%)80.6%
Memory size55.0 KiB
2023-12-12T19:13:07.536843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters9541
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique925 ?
Unique (%)67.9%

Sample

1st row39:34.0
2nd row44:08.0
3rd row29:05.0
4th row27:51.0
5th row30:38.0
ValueCountFrequency (%)
48:37.0 5
 
0.4%
54:14.0 4
 
0.3%
03:59.0 4
 
0.3%
04:31.0 4
 
0.3%
47:44.0 3
 
0.2%
28:08.0 3
 
0.2%
11:40.0 3
 
0.2%
13:10.0 3
 
0.2%
44:47.0 3
 
0.2%
19:54.0 3
 
0.2%
Other values (1119) 1328
97.4%
2023-12-12T19:13:08.057719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6815
71.4%
Other Punctuation 2726
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2154
31.6%
1 764
 
11.2%
4 755
 
11.1%
2 708
 
10.4%
3 699
 
10.3%
5 642
 
9.4%
7 294
 
4.3%
9 273
 
4.0%
6 268
 
3.9%
8 258
 
3.8%
Other Punctuation
ValueCountFrequency (%)
: 1363
50.0%
. 1363
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9541
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2154
22.6%
: 1363
14.3%
. 1363
14.3%
1 764
 
8.0%
4 755
 
7.9%
2 708
 
7.4%
3 699
 
7.3%
5 642
 
6.7%
7 294
 
3.1%
9 273
 
2.9%
Other values (2) 526
 
5.5%

RA_CERT_NO
Real number (ℝ)

MISSING 

Distinct803
Distinct (%)48.7%
Missing5374
Missing (%)76.5%
Infinite0
Infinite (%)0.0%
Mean505.47241
Minimum1
Maximum810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:13:08.274229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile68.4
Q1398
median562
Q3639
95-th percentile768
Maximum810
Range809
Interquartile range (IQR)241

Descriptive statistics

Standard deviation206.00529
Coefficient of variation (CV)0.40755002
Kurtosis-0.074401366
Mean505.47241
Median Absolute Deviation (MAD)88
Skewness-0.92704757
Sum833524
Variance42438.179
MonotonicityNot monotonic
2023-12-12T19:13:08.444249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
525 26
 
0.4%
554 20
 
0.3%
632 20
 
0.3%
535 19
 
0.3%
563 19
 
0.3%
555 18
 
0.3%
639 17
 
0.2%
1 16
 
0.2%
557 16
 
0.2%
597 15
 
0.2%
Other values (793) 1463
 
20.8%
(Missing) 5374
76.5%
ValueCountFrequency (%)
1 16
0.2%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
810 5
0.1%
809 6
0.1%
808 4
0.1%
807 3
< 0.1%
806 1
 
< 0.1%
805 1
 
< 0.1%
804 3
< 0.1%
803 2
 
< 0.1%
802 3
< 0.1%
801 4
0.1%

ER_EXAM_AVG
Real number (ℝ)

MISSING  ZEROS 

Distinct231
Distinct (%)4.0%
Missing1223
Missing (%)17.4%
Infinite0
Infinite (%)0.0%
Mean49.324293
Minimum0
Maximum100
Zeros680
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size61.9 KiB
2023-12-12T19:13:08.629948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q144
median54
Q362
95-th percentile75
Maximum100
Range100
Interquartile range (IQR)18

Descriptive statistics

Standard deviation21.05934
Coefficient of variation (CV)0.42695675
Kurtosis0.96268335
Mean49.324293
Median Absolute Deviation (MAD)9
Skewness-1.210115
Sum286080.9
Variance443.4958
MonotonicityNot monotonic
2023-12-12T19:13:08.801990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 680
 
9.7%
55.0 196
 
2.8%
60.0 158
 
2.2%
59.0 156
 
2.2%
50.0 153
 
2.2%
57.0 150
 
2.1%
52.0 148
 
2.1%
51.0 145
 
2.1%
54.0 143
 
2.0%
58.0 141
 
2.0%
Other values (221) 3730
53.1%
(Missing) 1223
 
17.4%
ValueCountFrequency (%)
0.0 680
9.7%
13.0 2
 
< 0.1%
16.0 1
 
< 0.1%
17.0 1
 
< 0.1%
18.0 2
 
< 0.1%
20.0 1
 
< 0.1%
21.0 1
 
< 0.1%
23.0 1
 
< 0.1%
25.0 3
 
< 0.1%
26.0 4
 
0.1%
ValueCountFrequency (%)
100.0 1
 
< 0.1%
96.0 1
 
< 0.1%
93.0 1
 
< 0.1%
91.0 1
 
< 0.1%
90.0 5
0.1%
89.0 5
0.1%
88.6 1
 
< 0.1%
88.0 1
 
< 0.1%
87.5 1
 
< 0.1%
87.0 7
0.1%

Sample

RECEIPT_SEQGROUP_NAMEGROUP_CODEES_YEARES_ORDERER_RECEIPT_NOER_REC_DATEER_USER_BIRTHER_USER_GENDERER_REC_TYPEER_STATUSER_PASS_YNER_CERT_YNER_CERT_NOER_CERT_TYPEER_EUNGSILYOIN_DTIMEUP_DTIMEER_EXAM_SUB_CNTER_EXAM_SUB1ER_EXAM_SUB2ER_EXAM_SUB3ER_EXAM_SUB4ER_EXAM_SUB5ER_EXAM_SUB6ER_EXAM_SUB7ER_EXAM_SUB8ER_EXAM_SUB9ER_EXAM_SUB10LAST_EDUHADICAP_YNHADICAP_FNAMEHADICAP_PATHLAST_EDU_NMLAST_EDU_DEPARTMENTGRADUATION_DATEEDU_EVIDENCE_FNAMEEDU_EVIDENCE_PATHTOTAL_CAREERCARR_EVIDENCE_FNAMECARR_EVIDENCE_PATHEXAM_QUALIFICATIONCHK_GRADERECEPTION_AGREEPOLICIES_AGREERECEPTION_AGREE_DATEPOLICIES_AGREE_DATERA_CERT_NOER_EXAM_AVG
01122014년 의료기기 RA 전문가 2급1402201421922014-11-031981-04-18방문수령접수완료YY126카드,상장무료38:00.444:39.05705580605000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>63.0
11132014년 의료기기 RA 전문가 2급1402201421932014-11-031988-11-21우편발송접수완료YY127카드,상장무료33:23.944:39.05707575706500000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>71.0
21142014년 의료기기 RA 전문가 2급140220141152014-11-031988-03-25우편발송접수완료YY10카드,상장무료34:07.052:05.25656580555000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>63.0
31152014년 의료기기 RA 전문가 2급140220141162014-11-031986-09-30우편발송접수완료YY11카드,상장무료33:36.233:26.05909095906500000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>86.0
41162014년 의료기기 RA 전문가 2급1402201421942014-11-031986-06-02우편발송접수완료YY128<NA>무료34:36.535:07.05709085807000000<NA>Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>79.0
51172014년 의료기기 RA 전문가 2급1402201421952014-11-031984-04-19우편발송접수완료YY129카드무료11:56.544:39.15855065605000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>62.0
61182014년 의료기기 RA 전문가 2급1402201421962014-11-031993-07-28우편발송접수완료NN<NA>카드,상장무료35:39.244:45.25554045255000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>43.0
71192014년 의료기기 RA 전문가 2급1402201421972014-11-031994-02-01우편발송접수완료NN<NA>카드,상장무료38:16.244:50.85453530654000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>43.0
81202014년 의료기기 RA 전문가 2급140220141<NA>2014-11-031965-09-23방문수령접수미승인<NA><NA><NA>카드,상장무료36:13.115:04.600000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0
91212014년 의료기기 RA 전문가 2급140220142<NA>2014-11-031987-01-02우편발송접수취소<NA><NA><NA>카드,상장무료37:07.239:40.000000000000<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0
RECEIPT_SEQGROUP_NAMEGROUP_CODEES_YEARES_ORDERER_RECEIPT_NOER_REC_DATEER_USER_BIRTHER_USER_GENDERER_REC_TYPEER_STATUSER_PASS_YNER_CERT_YNER_CERT_NOER_CERT_TYPEER_EUNGSILYOIN_DTIMEUP_DTIMEER_EXAM_SUB_CNTER_EXAM_SUB1ER_EXAM_SUB2ER_EXAM_SUB3ER_EXAM_SUB4ER_EXAM_SUB5ER_EXAM_SUB6ER_EXAM_SUB7ER_EXAM_SUB8ER_EXAM_SUB9ER_EXAM_SUB10LAST_EDUHADICAP_YNHADICAP_FNAMEHADICAP_PATHLAST_EDU_NMLAST_EDU_DEPARTMENTGRADUATION_DATEEDU_EVIDENCE_FNAMEEDU_EVIDENCE_PATHTOTAL_CAREERCARR_EVIDENCE_FNAMECARR_EVIDENCE_PATHEXAM_QUALIFICATIONCHK_GRADERECEPTION_AGREEPOLICIES_AGREERECEPTION_AGREE_DATEPOLICIES_AGREE_DATERA_CERT_NOER_EXAM_AVG
701367952020년 의료기기 RA 전문가 2급20022020359262020-05-251994-11-09우편발송접수완료YY<NA>상장5000059:30.035:47.056050656866<NA><NA><NA><NA><NA>대졸N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>12YY59:30.059:30.065161.8
701462162020년 의료기기 RA 전문가 2급20022020156942020-05-181982-01-03우편발송접수완료NY<NA><NA>5000008:43.030:56.053540502850<NA><NA><NA><NA><NA>대졸N<NA>/files/receipt/충남대학교화학(과·부)2007-02-23졸업증명서134.zip/files/receipt/<NA><NA><NA>22YY08:43.008:43.061340.6
701562182020년 의료기기 RA 전문가 2급20022020156922020-05-181989-05-23우편발송접수완료NY<NA>상장5000011:34.030:56.0500000<NA><NA><NA><NA><NA>대졸N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>12YY11:34.011:34.06130.0
701668002020년 의료기기 RA 전문가 2급20022020258312020-05-261986-05-01우편발송접수완료NY<NA>상장5000049:32.035:15.055045403830<NA><NA><NA><NA><NA>고졸N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>12YY49:32.049:32.063540.6
70177467[인허가] 필기(20)20112020162662020-08-041975-02-01우편발송접수완료<NA><NA><NA>상장5000001:30.011:36.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>석/박사N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>11YY01:30.001:30.0<NA><NA>
70187468[임상] 필기(20)20312020163112020-08-041981-04-10우편발송접수완료<NA><NA><NA><NA>5000007:50.008:33.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>석/박사N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>11YY07:50.007:50.0<NA><NA>
701962262020년 의료기기 RA 전문가 2급(완화)20032020161692020-05-181984-04-22우편발송접수완료NY<NA>상장1000013:04.055:59.025503500<NA><NA><NA><NA><NA>석/박사N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>02YY13:04.013:04.076345.0
702062282020년 의료기기 RA 전문가 2급(완화)20032020161682020-05-181987-01-02우편발송접수완료YY<NA>상장1000013:36.055:59.027006500<NA><NA><NA><NA><NA>석/박사N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>02YY13:36.013:36.076367.5
702162312020년 의료기기 RA 전문가 2급20022020156912020-05-181990-10-08우편발송접수완료NY<NA><NA>5000013:54.030:56.056060455359<NA><NA><NA><NA><NA>대졸N<NA>/files/receipt/연세대학교의용전자공학(과·전공)2016-08-26졸업증명서_임철현3.zip/files/receipt/<NA><NA><NA>22YY13:54.013:54.061355.4
702262382020년 의료기기 RA 전문가 2급(완화)20032020161672020-05-181980-12-05우편발송접수완료YY<NA>상장1000026:19.055:59.027508000<NA><NA><NA><NA><NA>석/박사N<NA>/files/receipt/<NA><NA><NA><NA><NA><NA><NA><NA>02YY26:19.026:19.076277.5