Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells1145
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory114.0 B

Variable types

Numeric2
Text4
Categorical6
Boolean1

Dataset

Description정부에서 독립운동 공적으로 서훈한 독립유공자 명단입니다.독립유공자의 관리번호, 성명, 생년월일, 사망년월일, 성별, 본적, 운동계열 등을 제공하고 있습니다.
Author국가보훈부
URLhttps://www.data.go.kr/data/15125208/fileData.do

Alerts

외국인여부 is highly overall correlated with 관리번호 and 3 other fieldsHigh correlation
운동계열 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
훈격(대분류) is highly overall correlated with 훈격(소분류)High correlation
훈격(소분류) is highly overall correlated with 훈격(대분류)High correlation
관리번호 is highly overall correlated with 포상년도 and 2 other fieldsHigh correlation
포상년도 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
본적(대분류) is highly overall correlated with 외국인여부High correlation
성별 is highly imbalanced (77.3%)Imbalance
외국인여부 is highly imbalanced (96.0%)Imbalance
본적(소분류) has 1145 (11.5%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 07:57:25.927004
Analysis finished2024-05-04 07:57:32.756727
Duration6.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307317.52
Minimum2
Maximum965906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:57:33.006999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1068.9
Q16317.25
median31486.5
Q3951507.75
95-th percentile960942.05
Maximum965906
Range965904
Interquartile range (IQR)945190.5

Descriptive statistics

Standard deviation432327.2
Coefficient of variation (CV)1.4067769
Kurtosis-1.3030498
Mean307317.52
Median Absolute Deviation (MAD)28727.5
Skewness0.82954995
Sum3.0731752 × 109
Variance1.8690681 × 1011
MonotonicityNot monotonic
2024-05-04T07:57:33.770331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36656 1
 
< 0.1%
954947 1
 
< 0.1%
6326 1
 
< 0.1%
6506 1
 
< 0.1%
6976 1
 
< 0.1%
7233 1
 
< 0.1%
954871 1
 
< 0.1%
965027 1
 
< 0.1%
9832 1
 
< 0.1%
953387 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
13 1
< 0.1%
18 1
< 0.1%
23 1
< 0.1%
27 1
< 0.1%
ValueCountFrequency (%)
965906 1
< 0.1%
965796 1
< 0.1%
965795 1
< 0.1%
965791 1
< 0.1%
965575 1
< 0.1%
965545 1
< 0.1%
965543 1
< 0.1%
965541 1
< 0.1%
965537 1
< 0.1%
965496 1
< 0.1%

성명
Text

Distinct9235
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:57:34.585402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.0016
Min length2

Characters and Unicode

Total characters30016
Distinct characters394
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8605 ?
Unique (%)86.1%

Sample

1st row조재창
2nd row신영묵
3rd row조창섭
4th row박병문
5th row김운배
ValueCountFrequency (%)
김용환 5
 
< 0.1%
김창환 5
 
< 0.1%
김봉수 5
 
< 0.1%
김상옥 4
 
< 0.1%
김동진 4
 
< 0.1%
김정기 4
 
< 0.1%
이기영 4
 
< 0.1%
김형석 4
 
< 0.1%
이병철 4
 
< 0.1%
김재명 4
 
< 0.1%
Other values (9266) 10006
99.6%
2024-05-04T07:57:35.982819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2053
 
6.8%
이 1637
 
5.5%
박 721
 
2.4%
정 689
 
2.3%
영 580
 
1.9%
성 523
 
1.7%
최 517
 
1.7%
기 439
 
1.5%
수 424
 
1.4%
윤 416
 
1.4%
Other values (384) 22017
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29967
99.8%
Space Separator 49
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2053
 
6.9%
이 1637
 
5.5%
박 721
 
2.4%
정 689
 
2.3%
영 580
 
1.9%
성 523
 
1.7%
최 517
 
1.7%
기 439
 
1.5%
수 424
 
1.4%
윤 416
 
1.4%
Other values (383) 21968
73.3%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29967
99.8%
Common 49
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2053
 
6.9%
이 1637
 
5.5%
박 721
 
2.4%
정 689
 
2.3%
영 580
 
1.9%
성 523
 
1.7%
최 517
 
1.7%
기 439
 
1.5%
수 424
 
1.4%
윤 416
 
1.4%
Other values (383) 21968
73.3%
Common
ValueCountFrequency (%)
49
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29967
99.8%
ASCII 49
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2053
 
6.9%
이 1637
 
5.5%
박 721
 
2.4%
정 689
 
2.3%
영 580
 
1.9%
성 523
 
1.7%
최 517
 
1.7%
기 439
 
1.5%
수 424
 
1.4%
윤 416
 
1.4%
Other values (383) 21968
73.3%
ASCII
ValueCountFrequency (%)
49
100.0%

생년월일
Text

Distinct5858
Distinct (%)58.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:57:36.884047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.3809
Min length2

Characters and Unicode

Total characters93809
Distinct characters16
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

Unique4842 ?
Unique (%)48.4%

Sample

1st row1887-05-12
2nd row1922-09-05
3rd row1912-10-18
4th row1886-08-14
5th row1888-11-27
ValueCountFrequency (%)
미상 773
 
7.7%
1882-00-00 96
 
1.0%
1881-00-00 95
 
0.9%
1880-00-00 90
 
0.9%
1883-00-00 89
 
0.9%
1879-00-00 82
 
0.8%
1884-00-00 79
 
0.8%
1878-00-00 69
 
0.7%
1877-00-00 68
 
0.7%
1885-00-00 68
 
0.7%
Other values (5848) 8491
84.9%
2024-05-04T07:57:38.352119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20311
21.7%
- 18452
19.7%
1 17085
18.2%
8 10944
11.7%
9 6976
 
7.4%
2 5485
 
5.8%
7 3343
 
3.6%
6 2638
 
2.8%
5 2504
 
2.7%
3 2351
 
2.5%
Other values (6) 3720
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73808
78.7%
Dash Punctuation 18452
 
19.7%
Other Letter 1549
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20311
27.5%
1 17085
23.1%
8 10944
14.8%
9 6976
 
9.5%
2 5485
 
7.4%
7 3343
 
4.5%
6 2638
 
3.6%
5 2504
 
3.4%
3 2351
 
3.2%
4 2171
 
2.9%
Other Letter
ValueCountFrequency (%)
미 773
49.9%
상 773
49.9%
비 1
 
0.1%
공 1
 
0.1%
개 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 18452
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92260
98.3%
Hangul 1549
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20311
22.0%
- 18452
20.0%
1 17085
18.5%
8 10944
11.9%
9 6976
 
7.6%
2 5485
 
5.9%
7 3343
 
3.6%
6 2638
 
2.9%
5 2504
 
2.7%
3 2351
 
2.5%
Hangul
ValueCountFrequency (%)
미 773
49.9%
상 773
49.9%
비 1
 
0.1%
공 1
 
0.1%
개 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92260
98.3%
Hangul 1549
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20311
22.0%
- 18452
20.0%
1 17085
18.5%
8 10944
11.9%
9 6976
 
7.6%
2 5485
 
5.9%
7 3343
 
3.6%
6 2638
 
2.9%
5 2504
 
2.7%
3 2351
 
2.5%
Hangul
ValueCountFrequency (%)
미 773
49.9%
상 773
49.9%
비 1
 
0.1%
공 1
 
0.1%
개 1
 
0.1%

사망년월일
Text

Distinct5889
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-04T07:57:39.164317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length7.8936
Min length2

Characters and Unicode

Total characters78936
Distinct characters15
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

Unique5100 ?
Unique (%)51.0%

Sample

1st row1956-05-30
2nd row1979-10-06
3rd row1969-03-18
4th row1955-02-24
5th row1966-07-15
ValueCountFrequency (%)
미상 2632
 
26.3%
1920-00-00 30
 
0.3%
1920-10-22 28
 
0.3%
1908-00-00 26
 
0.3%
1921-12-04 22
 
0.2%
1922-00-00 19
 
0.2%
1920-11-03 18
 
0.2%
1919-04-01 17
 
0.2%
1919-04-15 17
 
0.2%
1919-03-00 16
 
0.2%
Other values (5879) 7175
71.8%
2024-05-04T07:57:40.627447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 14734
18.7%
1 14363
18.2%
0 12592
16.0%
9 9434
12.0%
2 6155
7.8%
3 3145
 
4.0%
5 3016
 
3.8%
4 2942
 
3.7%
미 2632
 
3.3%
상 2632
 
3.3%
Other values (5) 7291
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58936
74.7%
Dash Punctuation 14734
 
18.7%
Other Letter 5266
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14363
24.4%
0 12592
21.4%
9 9434
16.0%
2 6155
10.4%
3 3145
 
5.3%
5 3016
 
5.1%
4 2942
 
5.0%
7 2505
 
4.3%
6 2448
 
4.2%
8 2336
 
4.0%
Other Letter
ValueCountFrequency (%)
미 2632
50.0%
상 2632
50.0%
생 1
 
< 0.1%
존 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 14734
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73670
93.3%
Hangul 5266
 
6.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 14734
20.0%
1 14363
19.5%
0 12592
17.1%
9 9434
12.8%
2 6155
8.4%
3 3145
 
4.3%
5 3016
 
4.1%
4 2942
 
4.0%
7 2505
 
3.4%
6 2448
 
3.3%
Hangul
ValueCountFrequency (%)
미 2632
50.0%
상 2632
50.0%
생 1
 
< 0.1%
존 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73670
93.3%
Hangul 5266
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 14734
20.0%
1 14363
19.5%
0 12592
17.1%
9 9434
12.8%
2 6155
8.4%
3 3145
 
4.3%
5 3016
 
4.1%
4 2942
 
4.0%
7 2505
 
3.4%
6 2448
 
3.3%
Hangul
ValueCountFrequency (%)
미 2632
50.0%
상 2632
50.0%
생 1
 
< 0.1%
존 1
 
< 0.1%

성별
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
9633 
여
 
367

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 9633
96.3%
여 367
 
3.7%

Length

2024-05-04T07:57:41.087165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:57:41.397779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 9633
96.3%
여 367
 
3.7%

본적(대분류)
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경상북도
1391 
충청남도
986 
미상
885 
전라남도
849 
경기도
813 
Other values (17)
5076 

Length

Max length4
Median length4
Mean length3.5867
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row충청남도
2nd row평안남도
3rd row전라남도
4th row충청남도
5th row충청남도

Common Values

ValueCountFrequency (%)
경상북도 1391
13.9%
충청남도 986
9.9%
미상 885
8.8%
전라남도 849
8.5%
경기도 813
8.1%
경상남도 797
8.0%
평안북도 761
7.6%
전라북도 637
 
6.4%
평안남도 566
 
5.7%
함경남도 473
 
4.7%
Other values (12) 1842
18.4%

Length

2024-05-04T07:57:41.883365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 1391
13.9%
충청남도 986
9.9%
미상 885
8.8%
전라남도 849
8.5%
경기도 813
8.1%
경상남도 797
8.0%
평안북도 761
7.6%
전라북도 637
 
6.4%
평안남도 566
 
5.7%
함경남도 473
 
4.7%
Other values (12) 1842
18.4%

본적(소분류)
Text

MISSING 

Distinct267
Distinct (%)3.0%
Missing1145
Missing (%)11.5%
Memory size156.2 KiB
2024-05-04T07:57:42.890676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.0042914
Min length2

Characters and Unicode

Total characters17748
Distinct characters151
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.2%

Sample

1st row청양
2nd row평원
3rd row영암
4th row공주
5th row아산
ValueCountFrequency (%)
안동 218
 
2.5%
기타 211
 
2.4%
청양 168
 
1.9%
홍성 139
 
1.6%
의주 138
 
1.6%
영덕 134
 
1.5%
평양 116
 
1.3%
서산 107
 
1.2%
의성 102
 
1.2%
안성 102
 
1.2%
Other values (257) 7420
83.8%
2024-05-04T07:57:44.278481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1213
 
6.8%
천 1059
 
6.0%
산 965
 
5.4%
성 945
 
5.3%
양 719
 
4.1%
안 650
 
3.7%
영 542
 
3.1%
원 482
 
2.7%
청 428
 
2.4%
동 427
 
2.4%
Other values (141) 10318
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17748
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1213
 
6.8%
천 1059
 
6.0%
산 965
 
5.4%
성 945
 
5.3%
양 719
 
4.1%
안 650
 
3.7%
영 542
 
3.1%
원 482
 
2.7%
청 428
 
2.4%
동 427
 
2.4%
Other values (141) 10318
58.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17748
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1213
 
6.8%
천 1059
 
6.0%
산 965
 
5.4%
성 945
 
5.3%
양 719
 
4.1%
안 650
 
3.7%
영 542
 
3.1%
원 482
 
2.7%
청 428
 
2.4%
동 427
 
2.4%
Other values (141) 10318
58.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17748
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1213
 
6.8%
천 1059
 
6.0%
산 965
 
5.4%
성 945
 
5.3%
양 719
 
4.1%
안 650
 
3.7%
영 542
 
3.1%
원 482
 
2.7%
청 428
 
2.4%
동 427
 
2.4%
Other values (141) 10318
58.1%

운동계열
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3.1운동
3495 
국내항일
1681 
의병
1509 
만주방면
1409 
학생운동
454 
Other values (11)
1452 

Length

Max length7
Median length6
Mean length4.0276
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.1운동
2nd row광복군
3rd row학생운동
4th row3.1운동
5th row3.1운동

Common Values

ValueCountFrequency (%)
3.1운동 3495
34.9%
국내항일 1681
16.8%
의병 1509
15.1%
만주방면 1409
14.1%
학생운동 454
 
4.5%
광복군 317
 
3.2%
미주방면 221
 
2.2%
임시정부 218
 
2.2%
일본방면 181
 
1.8%
중국방면 168
 
1.7%
Other values (6) 347
 
3.5%

Length

2024-05-04T07:57:44.829688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3.1운동 3495
34.9%
국내항일 1681
16.8%
의병 1509
15.1%
만주방면 1409
14.1%
학생운동 454
 
4.5%
광복군 317
 
3.2%
미주방면 221
 
2.2%
임시정부 218
 
2.2%
일본방면 181
 
1.8%
중국방면 168
 
1.7%
Other values (6) 347
 
3.5%

포상년도
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001.8771
Minimum1949
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-04T07:57:45.290063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1949
5-th percentile1990
Q11991
median2002
Q32014
95-th percentile2022
Maximum2024
Range75
Interquartile range (IQR)23

Descriptive statistics

Standard deviation13.810484
Coefficient of variation (CV)0.0068987672
Kurtosis0.19204473
Mean2001.8771
Median Absolute Deviation (MAD)12
Skewness-0.44104039
Sum20018771
Variance190.72947
MonotonicityNot monotonic
2024-05-04T07:57:45.730693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1990 2011
20.1%
1995 796
 
8.0%
1991 622
 
6.2%
2021 375
 
3.8%
2019 356
 
3.6%
2020 346
 
3.5%
2022 329
 
3.3%
2005 317
 
3.2%
1992 314
 
3.1%
2006 281
 
2.8%
Other values (42) 4253
42.5%
ValueCountFrequency (%)
1949 2
 
< 0.1%
1950 10
 
0.1%
1953 1
 
< 0.1%
1962 119
1.2%
1963 151
1.5%
1966 1
 
< 0.1%
1968 54
 
0.5%
1969 1
 
< 0.1%
1976 1
 
< 0.1%
1977 54
 
0.5%
ValueCountFrequency (%)
2024 60
 
0.6%
2023 152
1.5%
2022 329
3.3%
2021 375
3.8%
2020 346
3.5%
2019 356
3.6%
2018 198
2.0%
2017 134
 
1.3%
2016 176
1.8%
2015 267
2.7%

훈격(대분류)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
건국훈장
6555 
표창
2628 
포장
817 

Length

Max length4
Median length4
Mean length3.311
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row표창
2nd row건국훈장
3rd row표창
4th row표창
5th row표창

Common Values

ValueCountFrequency (%)
건국훈장 6555
65.5%
표창 2628
26.3%
포장 817
 
8.2%

Length

2024-05-04T07:57:46.190084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:57:46.559717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건국훈장 6555
65.5%
표창 2628
26.3%
포장 817
 
8.2%

훈격(소분류)
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
애족장
3515 
대통령표창
2628 
애국장
2505 
건국포장
817 
독립장
458 
Other values (2)
 
77

Length

Max length5
Median length3
Mean length3.6171
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대통령표창
2nd row애국장
3rd row대통령표창
4th row대통령표창
5th row대통령표창

Common Values

ValueCountFrequency (%)
애족장 3515
35.1%
대통령표창 2628
26.3%
애국장 2505
25.1%
건국포장 817
 
8.2%
독립장 458
 
4.6%
대통령장 56
 
0.6%
대한민국장 21
 
0.2%

Length

2024-05-04T07:57:46.946110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:57:47.281964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
애족장 3515
35.1%
대통령표창 2628
26.3%
애국장 2505
25.1%
건국포장 817
 
8.2%
독립장 458
 
4.6%
대통령장 56
 
0.6%
대한민국장 21
 
0.2%

훈장전수여부
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전수
6024 
미전수
3975 
비해당
 
1

Length

Max length3
Median length2
Mean length2.3976
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
전수 6024
60.2%
미전수 3975
39.8%
비해당 1
 
< 0.1%

Length

2024-05-04T07:57:47.606178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:57:47.787518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전수 6024
60.2%
미전수 3975
39.8%
비해당 1
 
< 0.1%

외국인여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9957 
True
 
43
ValueCountFrequency (%)
False 9957
99.6%
True 43
 
0.4%
2024-05-04T07:57:48.070283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-05-04T07:57:31.067342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:57:30.418839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:57:31.346223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:57:30.706997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T07:57:48.266118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호성별본적(대분류)운동계열포상년도훈격(대분류)훈격(소분류)훈장전수여부외국인여부
관리번호1.0000.0470.7010.7390.7790.4900.3800.4160.489
성별0.0471.0000.1490.3270.2280.0780.1250.0160.019
본적(대분류)0.7010.1491.0000.7230.4860.4170.4660.5730.984
운동계열0.7390.3270.7231.0000.5550.5670.5530.4661.000
포상년도0.7790.2280.4860.5551.0000.4850.6350.4820.717
훈격(대분류)0.4900.0780.4170.5670.4851.0001.0000.2500.022
훈격(소분류)0.3800.1250.4660.5530.6351.0001.0000.2610.194
훈장전수여부0.4160.0160.5730.4660.4820.2500.2611.0000.019
외국인여부0.4890.0190.9841.0000.7170.0220.1940.0191.000
2024-05-04T07:57:48.587744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별외국인여부운동계열훈격(대분류)훈장전수여부본적(대분류)훈격(소분류)
성별1.0000.0120.2570.1290.0260.1180.133
외국인여부0.0121.0000.9990.0370.0320.8990.207
운동계열0.2570.9991.0000.3740.2880.3100.292
훈격(대분류)0.1290.0370.3741.0000.0810.2401.000
훈장전수여부0.0260.0320.2880.0811.0000.3640.181
본적(대분류)0.1180.8990.3100.2400.3641.0000.219
훈격(소분류)0.1330.2070.2921.0000.1810.2191.000
2024-05-04T07:57:48.897779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호포상년도성별본적(대분류)운동계열훈격(대분류)훈격(소분류)훈장전수여부외국인여부
관리번호1.0000.7350.0780.4900.5560.1970.2770.1550.747
포상년도0.7351.0000.1750.1940.2460.3330.3930.3310.524
성별0.0780.1751.0000.1180.2570.1290.1330.0260.012
본적(대분류)0.4900.1940.1181.0000.3100.2400.2190.3640.899
운동계열0.5560.2460.2570.3101.0000.3740.2920.2880.999
훈격(대분류)0.1970.3330.1290.2400.3741.0001.0000.0810.037
훈격(소분류)0.2770.3930.1330.2190.2921.0001.0000.1810.207
훈장전수여부0.1550.3310.0260.3640.2880.0810.1811.0000.032
외국인여부0.7470.5240.0120.8990.9990.0370.2070.0321.000

Missing values

2024-05-04T07:57:31.877883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:57:32.484082image/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.

Sample

관리번호성명생년월일사망년월일성별본적(대분류)본적(소분류)운동계열포상년도훈격(대분류)훈격(소분류)훈장전수여부외국인여부
1044136656조재창1887-05-121956-05-30남충청남도청양3.1운동2019표창대통령표창전수N
63578481신영묵1922-09-051979-10-06남평안남도평원광복군1990건국훈장애국장전수N
1112450835조창섭1912-10-181969-03-18남전라남도영암학생운동2018표창대통령표창전수N
1005434486박병문1886-08-141955-02-24남충청남도공주3.1운동2020표창대통령표창전수N
16224957421김운배1888-11-271966-07-15남충청남도아산3.1운동2021표창대통령표창전수N
13579951588김화서1886-00-00미상남충청북도충주의병2014건국훈장애국장미전수N
11611421감익룡1887-12-291946-09-00남황해도송화계몽운동1990건국훈장애족장전수N
72629584박수찬1867-10-271922-08-14남경상북도청송의병2010포장건국포장전수N
1241990302마뇌병1888-06-291950-06-25남강원도춘천국내항일2012포장건국포장전수N
20502679정성언1892-07-071952-02-03남경상남도동래3.1운동1993표창대통령표창전수N
관리번호성명생년월일사망년월일성별본적(대분류)본적(소분류)운동계열포상년도훈격(대분류)훈격(소분류)훈장전수여부외국인여부
13028950534김원식1858-00-001907-12-14남미상<NA>의병2003건국훈장애국장미전수N
33654664송훈익1884-09-221961-02-27남경상북도성주3.1운동1990건국훈장애족장전수N
875430666김성실1869-04-031931-01-25남경기도수원3.1운동2007표창대통령표창전수N
15544956082홍익삼1888-06-20미상남서울<NA>미주방면2020포장건국포장미전수N
13577951585모명순1879-00-00미상남충청북도괴산의병2014건국훈장애족장미전수N
53447365유상1890-08-301950-07-10남전라북도정읍국내항일2005표창대통령표창전수N
1079642374최경훈1867-00-00미상남평안남도성천국내항일2010포장건국포장미전수N
13251950822안수갑1897-11-211973-09-27남경상북도달성국내항일2018건국훈장애족장전수N
11891459이석근1885-11-271947-02-17남경기도안성3.1운동1990건국훈장애족장전수N
861330227권재갑1900-03-27미상남경상북도달성3.1운동2020표창대통령표창미전수N