Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells874
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory115.0 B

Variable types

Numeric3
Text8
Boolean2

Dataset

Description독립운동가의 인적사항과 당시 활동상을 확인하기 위해서는 판결문이나 재소자 신분카드,범죄인 명부,수형인 명부,당시의 기관지,정보 보고서, 신문 등이 많이 활용됩니다. 그러나 사학을 전공한 전문가가 아닌 일반 개인이 이런 자료를 찾고 확인하기란 쉬운 일이 아니며, 검색채널 또한 제한적입니다. 따라서,국가기록원에 소장중인 형사사건 판결문 중 독립운동 관련 판결문을 선별하고, 내용 이해를 돕기 위해 판결주문을 번역, 사건개요 및 주제어 등을 작성하여 일반국민들과 학술연구자들이 보다 쉽게 검색 활용할 수 있게 하기 위해 본 콘텐츠을 구축하였습니다.
Author행정안전부 국가기록원
URLhttps://www.data.go.kr/data/15084333/fileData.do

Alerts

판결문_원문_제공 is highly imbalanced (98.7%)Imbalance
판결문_번역본_제공 is highly imbalanced (95.6%)Imbalance
사건개요 has 844 (8.4%) missing valuesMissing
마이크로필름번호 is highly skewed (γ1 = 60.53749223)Skewed
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:17:30.252581
Analysis finished2023-12-12 18:17:34.355955
Duration4.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9530.3063
Minimum1
Maximum19167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:17:34.444716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile931.8
Q14802.75
median9464.5
Q314256.25
95-th percentile18208.05
Maximum19167
Range19166
Interquartile range (IQR)9453.5

Descriptive statistics

Standard deviation5497.3614
Coefficient of variation (CV)0.57682946
Kurtosis-1.1805993
Mean9530.3063
Median Absolute Deviation (MAD)4725.5
Skewness0.0058705807
Sum95303063
Variance30220982
MonotonicityNot monotonic
2023-12-13T03:17:34.596857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3794 1
 
< 0.1%
10064 1
 
< 0.1%
10965 1
 
< 0.1%
4363 1
 
< 0.1%
3109 1
 
< 0.1%
8518 1
 
< 0.1%
5359 1
 
< 0.1%
10586 1
 
< 0.1%
11498 1
 
< 0.1%
2900 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
21 1
< 0.1%
ValueCountFrequency (%)
19167 1
< 0.1%
19166 1
< 0.1%
19165 1
< 0.1%
19164 1
< 0.1%
19159 1
< 0.1%
19157 1
< 0.1%
19156 1
< 0.1%
19154 1
< 0.1%
19153 1
< 0.1%
19149 1
< 0.1%
Distinct7888
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:17:34.852793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length9
Mean length10.2807
Min length7

Characters and Unicode

Total characters102807
Distinct characters1635
Distinct categories11 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6185 ?
Unique (%)61.9%

Sample

1st row김응하(金應河)
2nd row최종하(崔宗河)
3rd row정봉조(鄭鳳朝)
4th row이채룡(李彩龍)
5th row이중식(李仲植)
ValueCountFrequency (%)
양전백(梁甸伯 7
 
0.1%
최경호(崔京鎬 6
 
0.1%
안경수(安敬秀 6
 
0.1%
여도현(呂道鉉 6
 
0.1%
김원배(金元培 6
 
0.1%
김봉수(金鳳洙 6
 
0.1%
김학수(金學洙 6
 
0.1%
김윤식(金允植 6
 
0.1%
김병기(金炳基 5
 
< 0.1%
양기탁(梁起鐸 5
 
< 0.1%
Other values (7889) 10006
99.4%
2023-12-13T03:17:35.571425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 11719
 
11.4%
) 11716
 
11.4%
8505
 
8.3%
2309
 
2.2%
2304
 
2.2%
1929
 
1.9%
1813
 
1.8%
820
 
0.8%
815
 
0.8%
794
 
0.8%
Other values (1625) 60083
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70424
68.5%
Open Punctuation 11719
 
11.4%
Close Punctuation 11716
 
11.4%
Space Separator 8505
 
8.3%
Decimal Number 153
 
0.1%
Connector Punctuation 102
 
0.1%
Other Punctuation 53
 
0.1%
Uppercase Letter 51
 
< 0.1%
Lowercase Letter 51
 
< 0.1%
Other Symbol 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2309
 
3.3%
2304
 
3.3%
1929
 
2.7%
1813
 
2.6%
820
 
1.2%
815
 
1.2%
794
 
1.1%
689
 
1.0%
656
 
0.9%
588
 
0.8%
Other values (1614) 57707
81.9%
Other Punctuation
ValueCountFrequency (%)
, 52
98.1%
/ 1
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 11719
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11716
100.0%
Space Separator
ValueCountFrequency (%)
8505
100.0%
Decimal Number
ValueCountFrequency (%)
0 153
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 102
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 51
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 51
100.0%
Other Symbol
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35314
34.3%
Han 35095
34.1%
Common 32281
31.4%
Latin 102
 
0.1%
Katakana 15
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
2309
 
6.6%
1813
 
5.2%
815
 
2.3%
543
 
1.5%
419
 
1.2%
340
 
1.0%
319
 
0.9%
311
 
0.9%
302
 
0.9%
296
 
0.8%
Other values (1256) 27628
78.7%
Hangul
ValueCountFrequency (%)
2304
 
6.5%
1929
 
5.5%
820
 
2.3%
794
 
2.2%
689
 
2.0%
656
 
1.9%
588
 
1.7%
550
 
1.6%
543
 
1.5%
489
 
1.4%
Other values (334) 25952
73.5%
Katakana
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Common
ValueCountFrequency (%)
( 11719
36.3%
) 11716
36.3%
8505
26.3%
0 153
 
0.5%
_ 102
 
0.3%
, 52
 
0.2%
31
 
0.1%
- 2
 
< 0.1%
/ 1
 
< 0.1%
Latin
ValueCountFrequency (%)
D 51
50.0%
x 51
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35314
34.3%
ASCII 32352
31.5%
CJK 32079
31.2%
CJK Compat Ideographs 3016
 
2.9%
Geometric Shapes 31
 
< 0.1%
Katakana 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 11719
36.2%
) 11716
36.2%
8505
26.3%
0 153
 
0.5%
_ 102
 
0.3%
, 52
 
0.2%
D 51
 
0.2%
x 51
 
0.2%
- 2
 
< 0.1%
/ 1
 
< 0.1%
CJK
ValueCountFrequency (%)
2309
 
7.2%
815
 
2.5%
543
 
1.7%
419
 
1.3%
340
 
1.1%
319
 
1.0%
311
 
1.0%
302
 
0.9%
296
 
0.9%
294
 
0.9%
Other values (1196) 26131
81.5%
Hangul
ValueCountFrequency (%)
2304
 
6.5%
1929
 
5.5%
820
 
2.3%
794
 
2.2%
689
 
2.0%
656
 
1.9%
588
 
1.7%
550
 
1.6%
543
 
1.5%
489
 
1.4%
Other values (334) 25952
73.5%
CJK Compat Ideographs
ValueCountFrequency (%)
1813
60.1%
167
 
5.5%
137
 
4.5%
118
 
3.9%
109
 
3.6%
106
 
3.5%
76
 
2.5%
61
 
2.0%
52
 
1.7%
44
 
1.5%
Other values (50) 333
 
11.0%
Geometric Shapes
ValueCountFrequency (%)
31
100.0%
Katakana
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Distinct1801
Distinct (%)18.0%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T03:17:35.962220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length3
Mean length4.7992796
Min length2

Characters and Unicode

Total characters47964
Distinct characters32
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1476 ?
Unique (%)14.8%

Sample

1st row63세
2nd row43세
3rd row31세
4th row40세
5th row40세
ValueCountFrequency (%)
22세 387
 
3.3%
24세 379
 
3.2%
23세 374
 
3.2%
25세 359
 
3.1%
21세 358
 
3.1%
26세 351
 
3.0%
30세 341
 
2.9%
27세 340
 
2.9%
29세 336
 
2.9%
20세 313
 
2.7%
Other values (902) 8199
69.9%
2023-12-13T03:17:36.475781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9975
20.8%
2 6654
13.9%
3 4152
 
8.7%
1 3739
 
7.8%
4 2533
 
5.3%
) 2036
 
4.2%
( 2033
 
4.2%
2031
 
4.2%
2026
 
4.2%
1981
 
4.1%
Other values (22) 10804
22.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26035
54.3%
Other Letter 16112
33.6%
Close Punctuation 2036
 
4.2%
Open Punctuation 2033
 
4.2%
Space Separator 1744
 
3.6%
Other Punctuation 3
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9975
61.9%
2031
 
12.6%
2026
 
12.6%
1981
 
12.3%
45
 
0.3%
20
 
0.1%
14
 
0.1%
6
 
< 0.1%
4
 
< 0.1%
2
 
< 0.1%
Other values (6) 8
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 6654
25.6%
3 4152
15.9%
1 3739
14.4%
4 2533
 
9.7%
5 1850
 
7.1%
0 1526
 
5.9%
6 1478
 
5.7%
9 1429
 
5.5%
8 1365
 
5.2%
7 1309
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2036
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2033
100.0%
Space Separator
ValueCountFrequency (%)
1744
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31852
66.4%
Hangul 16103
33.6%
Han 9
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6654
20.9%
3 4152
13.0%
1 3739
11.7%
4 2533
 
8.0%
) 2036
 
6.4%
( 2033
 
6.4%
5 1850
 
5.8%
1744
 
5.5%
0 1526
 
4.8%
6 1478
 
4.6%
Other values (6) 4107
12.9%
Hangul
ValueCountFrequency (%)
9975
61.9%
2031
 
12.6%
2026
 
12.6%
1981
 
12.3%
45
 
0.3%
20
 
0.1%
14
 
0.1%
6
 
< 0.1%
4
 
< 0.1%
1
 
< 0.1%
Han
ValueCountFrequency (%)
2
22.2%
2
22.2%
2
22.2%
1
11.1%
1
11.1%
1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31851
66.4%
Hangul 16103
33.6%
CJK 9
 
< 0.1%
Geometric Shapes 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
9975
61.9%
2031
 
12.6%
2026
 
12.6%
1981
 
12.3%
45
 
0.3%
20
 
0.1%
14
 
0.1%
6
 
< 0.1%
4
 
< 0.1%
1
 
< 0.1%
ASCII
ValueCountFrequency (%)
2 6654
20.9%
3 4152
13.0%
1 3739
11.7%
4 2533
 
8.0%
) 2036
 
6.4%
( 2033
 
6.4%
5 1850
 
5.8%
1744
 
5.5%
0 1526
 
4.8%
6 1478
 
4.6%
Other values (5) 4106
12.9%
CJK
ValueCountFrequency (%)
2
22.2%
2
22.2%
2
22.2%
1
11.1%
1
11.1%
1
11.1%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%
Distinct6804
Distinct (%)68.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:17:36.878414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length17.0037
Min length2

Characters and Unicode

Total characters170037
Distinct characters571
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5344 ?
Unique (%)53.4%

Sample

1st row황해도 수안군 수안면 석교리
2nd row강원도 횡성군 횡성면 읍상리
3rd row지나 간도 장백현 16도구 서덕수
4th row황해도 수안군 수안면 자의리
5th row경북 영덕군 영해면 묘곡동
ValueCountFrequency (%)
경기도 1353
 
3.2%
전라남도 1173
 
2.7%
번지 950
 
2.2%
경상북도 878
 
2.0%
경성부 878
 
2.0%
전라북도 694
 
1.6%
강원도 553
 
1.3%
경북 547
 
1.3%
황해도 516
 
1.2%
함경남도 438
 
1.0%
Other values (7268) 34965
81.4%
2023-12-13T03:17:37.475043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33020
 
19.4%
8221
 
4.8%
8066
 
4.7%
7888
 
4.6%
6100
 
3.6%
5013
 
2.9%
4454
 
2.6%
4018
 
2.4%
3953
 
2.3%
3770
 
2.2%
Other values (561) 85534
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124448
73.2%
Space Separator 33020
 
19.4%
Decimal Number 12018
 
7.1%
Close Punctuation 219
 
0.1%
Open Punctuation 219
 
0.1%
Dash Punctuation 104
 
0.1%
Other Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8221
 
6.6%
8066
 
6.5%
7888
 
6.3%
6100
 
4.9%
5013
 
4.0%
4454
 
3.6%
4018
 
3.2%
3953
 
3.2%
3770
 
3.0%
3686
 
3.0%
Other values (546) 69279
55.7%
Decimal Number
ValueCountFrequency (%)
1 2177
18.1%
2 1687
14.0%
3 1322
11.0%
4 1241
10.3%
5 1132
9.4%
7 975
8.1%
6 967
8.0%
9 909
7.6%
8 830
 
6.9%
0 778
 
6.5%
Space Separator
ValueCountFrequency (%)
33020
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%
Other Symbol
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123915
72.9%
Common 45589
 
26.8%
Han 533
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8221
 
6.6%
8066
 
6.5%
7888
 
6.4%
6100
 
4.9%
5013
 
4.0%
4454
 
3.6%
4018
 
3.2%
3953
 
3.2%
3770
 
3.0%
3686
 
3.0%
Other values (384) 68746
55.5%
Han
ValueCountFrequency (%)
110
20.6%
110
20.6%
18
 
3.4%
11
 
2.1%
9
 
1.7%
9
 
1.7%
9
 
1.7%
7
 
1.3%
6
 
1.1%
5
 
0.9%
Other values (152) 239
44.8%
Common
ValueCountFrequency (%)
33020
72.4%
1 2177
 
4.8%
2 1687
 
3.7%
3 1322
 
2.9%
4 1241
 
2.7%
5 1132
 
2.5%
7 975
 
2.1%
6 967
 
2.1%
9 909
 
2.0%
8 830
 
1.8%
Other values (5) 1329
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123915
72.9%
ASCII 45580
 
26.8%
CJK 508
 
0.3%
CJK Compat Ideographs 25
 
< 0.1%
Geometric Shapes 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33020
72.4%
1 2177
 
4.8%
2 1687
 
3.7%
3 1322
 
2.9%
4 1241
 
2.7%
5 1132
 
2.5%
7 975
 
2.1%
6 967
 
2.1%
9 909
 
2.0%
8 830
 
1.8%
Other values (4) 1320
 
2.9%
Hangul
ValueCountFrequency (%)
8221
 
6.6%
8066
 
6.5%
7888
 
6.4%
6100
 
4.9%
5013
 
4.0%
4454
 
3.6%
4018
 
3.2%
3953
 
3.2%
3770
 
3.0%
3686
 
3.0%
Other values (384) 68746
55.5%
CJK
ValueCountFrequency (%)
110
21.7%
110
21.7%
18
 
3.5%
11
 
2.2%
9
 
1.8%
9
 
1.8%
9
 
1.8%
5
 
1.0%
5
 
1.0%
5
 
1.0%
Other values (141) 217
42.7%
Geometric Shapes
ValueCountFrequency (%)
9
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
7
28.0%
6
24.0%
3
12.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%

죄명
Text

Distinct689
Distinct (%)6.9%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T03:17:37.795973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length63
Mean length10.130443
Min length2

Characters and Unicode

Total characters101193
Distinct characters196
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique344 ?
Unique (%)3.4%

Sample

1st row내란
2nd row보안법위반
3rd row대정8년 제령 제7호 위반, 폭발물취체벌칙위반, 강도살인, 상인방조, 불법체포, 감금, 상해
4th row내란
5th row소요, 공무집행방해, 건조물손괴, 기물손괴, 공문서훼기, 상해, 보안법위반
ValueCountFrequency (%)
보안법위반 5360
25.2%
소요 1722
 
8.1%
치안유지법위반 1271
 
6.0%
출판법위반 1168
 
5.5%
위반 1078
 
5.1%
대정8년 1032
 
4.9%
제령 1030
 
4.8%
제7호 1019
 
4.8%
강도 634
 
3.0%
내란 384
 
1.8%
Other values (266) 6550
30.8%
2023-12-13T03:17:38.308492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11259
 
11.1%
10109
 
10.0%
9789
 
9.7%
8404
 
8.3%
6925
 
6.8%
, 6673
 
6.6%
5564
 
5.5%
2089
 
2.1%
1855
 
1.8%
1723
 
1.7%
Other values (186) 36803
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81073
80.1%
Space Separator 11259
 
11.1%
Other Punctuation 6673
 
6.6%
Decimal Number 2160
 
2.1%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10109
 
12.5%
9789
 
12.1%
8404
 
10.4%
6925
 
8.5%
5564
 
6.9%
2089
 
2.6%
1855
 
2.3%
1723
 
2.1%
1590
 
2.0%
1475
 
1.8%
Other values (172) 31550
38.9%
Decimal Number
ValueCountFrequency (%)
8 1051
48.7%
7 1026
47.5%
6 36
 
1.7%
3 26
 
1.2%
1 7
 
0.3%
4 6
 
0.3%
9 3
 
0.1%
2 2
 
0.1%
0 2
 
0.1%
5 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
11259
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6673
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81073
80.1%
Common 20120
 
19.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10109
 
12.5%
9789
 
12.1%
8404
 
10.4%
6925
 
8.5%
5564
 
6.9%
2089
 
2.6%
1855
 
2.3%
1723
 
2.1%
1590
 
2.0%
1475
 
1.8%
Other values (172) 31550
38.9%
Common
ValueCountFrequency (%)
11259
56.0%
, 6673
33.2%
8 1051
 
5.2%
7 1026
 
5.1%
6 36
 
0.2%
3 26
 
0.1%
( 14
 
0.1%
) 14
 
0.1%
1 7
 
< 0.1%
4 6
 
< 0.1%
Other values (4) 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81073
80.1%
ASCII 20120
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11259
56.0%
, 6673
33.2%
8 1051
 
5.2%
7 1026
 
5.1%
6 36
 
0.2%
3 26
 
0.1%
( 14
 
0.1%
) 14
 
0.1%
1 7
 
< 0.1%
4 6
 
< 0.1%
Other values (4) 8
 
< 0.1%
Hangul
ValueCountFrequency (%)
10109
 
12.5%
9789
 
12.1%
8404
 
10.4%
6925
 
8.5%
5564
 
6.9%
2089
 
2.6%
1855
 
2.3%
1723
 
2.1%
1590
 
2.0%
1475
 
1.8%
Other values (172) 31550
38.9%

주문
Text

Distinct1444
Distinct (%)14.4%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T03:17:38.559323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length137
Median length83
Mean length12.010701
Min length2

Characters and Unicode

Total characters120095
Distinct characters291
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique860 ?
Unique (%)8.6%

Sample

1st row관할재판소를 경성지방법원으로 지정
2nd row징역 6월
3rd row징역 10년
4th row관할재판소를 경성지방법원으로 지정
5th row징역 6월
ValueCountFrequency (%)
징역 4920
 
15.0%
기각 2605
 
8.0%
상고 1772
 
5.4%
취소 1184
 
3.6%
산입 1178
 
3.6%
본형에 1176
 
3.6%
6월 1124
 
3.4%
1년 1099
 
3.4%
공소 847
 
2.6%
미결구류일수 842
 
2.6%
Other values (879) 15961
48.8%
2023-12-13T03:17:38.938344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22778
 
19.0%
5075
 
4.2%
4980
 
4.1%
3959
 
3.3%
3263
 
2.7%
3116
 
2.6%
2907
 
2.4%
2832
 
2.4%
2826
 
2.4%
0 2768
 
2.3%
Other values (281) 65591
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80386
66.9%
Space Separator 22778
 
19.0%
Decimal Number 12648
 
10.5%
Close Punctuation 1604
 
1.3%
Open Punctuation 1602
 
1.3%
Other Punctuation 1077
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5075
 
6.3%
4980
 
6.2%
3959
 
4.9%
3263
 
4.1%
3116
 
3.9%
2907
 
3.6%
2832
 
3.5%
2826
 
3.5%
2714
 
3.4%
2372
 
3.0%
Other values (264) 46342
57.6%
Decimal Number
ValueCountFrequency (%)
0 2768
21.9%
1 2615
20.7%
6 2056
16.3%
2 1424
11.3%
3 1128
8.9%
5 901
 
7.1%
8 620
 
4.9%
4 509
 
4.0%
9 375
 
3.0%
7 252
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 1601
99.8%
] 3
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1599
99.8%
[ 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1068
99.2%
. 9
 
0.8%
Space Separator
ValueCountFrequency (%)
22778
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79808
66.5%
Common 39709
33.1%
Han 578
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5075
 
6.4%
4980
 
6.2%
3959
 
5.0%
3263
 
4.1%
3116
 
3.9%
2907
 
3.6%
2832
 
3.5%
2826
 
3.5%
2714
 
3.4%
2372
 
3.0%
Other values (237) 45764
57.3%
Han
ValueCountFrequency (%)
120
20.8%
62
10.7%
45
 
7.8%
45
 
7.8%
45
 
7.8%
45
 
7.8%
39
 
6.7%
35
 
6.1%
24
 
4.2%
24
 
4.2%
Other values (17) 94
16.3%
Common
ValueCountFrequency (%)
22778
57.4%
0 2768
 
7.0%
1 2615
 
6.6%
6 2056
 
5.2%
) 1601
 
4.0%
( 1599
 
4.0%
2 1424
 
3.6%
3 1128
 
2.8%
, 1068
 
2.7%
5 901
 
2.3%
Other values (7) 1771
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79808
66.5%
ASCII 39709
33.1%
CJK 433
 
0.4%
CJK Compat Ideographs 145
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22778
57.4%
0 2768
 
7.0%
1 2615
 
6.6%
6 2056
 
5.2%
) 1601
 
4.0%
( 1599
 
4.0%
2 1424
 
3.6%
3 1128
 
2.8%
, 1068
 
2.7%
5 901
 
2.3%
Other values (7) 1771
 
4.5%
Hangul
ValueCountFrequency (%)
5075
 
6.4%
4980
 
6.2%
3959
 
5.0%
3263
 
4.1%
3116
 
3.9%
2907
 
3.6%
2832
 
3.5%
2826
 
3.5%
2714
 
3.4%
2372
 
3.0%
Other values (237) 45764
57.3%
CJK Compat Ideographs
ValueCountFrequency (%)
120
82.8%
22
 
15.2%
3
 
2.1%
CJK
ValueCountFrequency (%)
62
14.3%
45
10.4%
45
10.4%
45
10.4%
45
10.4%
39
9.0%
35
8.1%
24
 
5.5%
24
 
5.5%
22
 
5.1%
Other values (14) 47
10.9%
Distinct1836
Distinct (%)18.4%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T03:17:39.184111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters219890
Distinct characters15
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

Unique891 ?
Unique (%)8.9%

Sample

1st row1920-03-22 오전 12:00:00
2nd row1919-06-09 오전 12:00:00
3rd row1924-03-24 오전 12:00:00
4th row1920-03-22 오전 12:00:00
5th row1919-06-05 오전 12:00:00
ValueCountFrequency (%)
오전 9995
33.3%
12:00:00 9995
33.3%
1920-03-22 187
 
0.6%
1919-08-30 166
 
0.6%
1919-11-06 130
 
0.4%
1919-05-31 103
 
0.3%
1919-07-05 92
 
0.3%
1919-07-12 90
 
0.3%
1919-06-05 89
 
0.3%
1919-06-12 80
 
0.3%
Other values (1828) 9058
30.2%
2023-12-13T03:17:39.525209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 54268
24.7%
1 33424
15.2%
- 19990
 
9.1%
19990
 
9.1%
: 19990
 
9.1%
2 18251
 
8.3%
9 16954
 
7.7%
9995
 
4.5%
9995
 
4.5%
3 4343
 
2.0%
Other values (5) 12690
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 139930
63.6%
Dash Punctuation 19990
 
9.1%
Space Separator 19990
 
9.1%
Other Punctuation 19990
 
9.1%
Other Letter 19990
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 54268
38.8%
1 33424
23.9%
2 18251
 
13.0%
9 16954
 
12.1%
3 4343
 
3.1%
4 2696
 
1.9%
5 2648
 
1.9%
7 2521
 
1.8%
8 2425
 
1.7%
6 2400
 
1.7%
Other Letter
ValueCountFrequency (%)
9995
50.0%
9995
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 19990
100.0%
Space Separator
ValueCountFrequency (%)
19990
100.0%
Other Punctuation
ValueCountFrequency (%)
: 19990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 199900
90.9%
Hangul 19990
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 54268
27.1%
1 33424
16.7%
- 19990
 
10.0%
19990
 
10.0%
: 19990
 
10.0%
2 18251
 
9.1%
9 16954
 
8.5%
3 4343
 
2.2%
4 2696
 
1.3%
5 2648
 
1.3%
Other values (3) 7346
 
3.7%
Hangul
ValueCountFrequency (%)
9995
50.0%
9995
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199900
90.9%
Hangul 19990
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 54268
27.1%
1 33424
16.7%
- 19990
 
10.0%
19990
 
10.0%
: 19990
 
10.0%
2 18251
 
9.1%
9 16954
 
8.5%
3 4343
 
2.2%
4 2696
 
1.3%
5 2648
 
1.3%
Other values (3) 7346
 
3.7%
Hangul
ValueCountFrequency (%)
9995
50.0%
9995
50.0%

사건개요
Text

MISSING 

Distinct3917
Distinct (%)42.8%
Missing844
Missing (%)8.4%
Memory size156.2 KiB
2023-12-13T03:17:39.811897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length262
Median length160
Mean length62.879314
Min length1

Characters and Unicode

Total characters575723
Distinct characters872
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2690 ?
Unique (%)29.4%

Sample

1st row천도교도들이 독립선언서를 인쇄배포하고 군중이 시위하며 헌병분대내로 난입 하자 발포저지하였다.
2nd row조선 독립선언서 12장을 교부받아 신재근, 김인경에게 취지를 말하고 교부하였다.
3rd row지나에서 광정단을 조직하고 조선독립운도에 종사하여 광정단원 40여명이 군자금및 무기약탈을 목적으로 조선 내로 침입하고 영성경찰관주재소를 습격하여 순사를 살해하고 다른 2명의 순사에게 중상을 입히는 사건을 방조, 밀정자를 감금, 구타하였다.
4th row천도교도들이 독립선언서를 인쇄배포하고 군중이 시위하며 헌병분대내로 난입 하자 발포저지하였다.
5th row성내동에서 이천여명의 군중과 같이 한국독립만세를 부르고 시장 부근을 행진하였다.
ValueCountFrequency (%)
조선독립만세를 2010
 
1.7%
함께 1232
 
1.0%
군중과 1011
 
0.8%
자이다 918
 
0.8%
하였다 892
 
0.7%
치안을 859
 
0.7%
독립만세를 734
 
0.6%
목적으로 696
 
0.6%
관련건 674
 
0.6%
방해한 650
 
0.5%
Other values (18116) 110261
91.9%
2023-12-13T03:17:40.257257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
111952
 
19.4%
20958
 
3.6%
12766
 
2.2%
12690
 
2.2%
9570
 
1.7%
9454
 
1.6%
9284
 
1.6%
9099
 
1.6%
8726
 
1.5%
8538
 
1.5%
Other values (862) 362686
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428835
74.5%
Space Separator 111952
 
19.4%
Decimal Number 16243
 
2.8%
Other Punctuation 14899
 
2.6%
Uppercase Letter 3373
 
0.6%
Final Punctuation 101
 
< 0.1%
Initial Punctuation 87
 
< 0.1%
Open Punctuation 60
 
< 0.1%
Close Punctuation 59
 
< 0.1%
Lowercase Letter 45
 
< 0.1%
Other values (4) 69
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20958
 
4.9%
12766
 
3.0%
12690
 
3.0%
9570
 
2.2%
9454
 
2.2%
9284
 
2.2%
9099
 
2.1%
8726
 
2.0%
8538
 
2.0%
8271
 
1.9%
Other values (820) 319479
74.5%
Decimal Number
ValueCountFrequency (%)
0 6745
41.5%
1 2826
17.4%
3 1200
 
7.4%
2 1190
 
7.3%
4 1063
 
6.5%
9 1058
 
6.5%
7 787
 
4.8%
5 671
 
4.1%
6 377
 
2.3%
8 326
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
C 1119
33.2%
A 1118
33.1%
J 1117
33.1%
H 7
 
0.2%
M 7
 
0.2%
S 2
 
0.1%
K 1
 
< 0.1%
R 1
 
< 0.1%
L 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 8270
55.5%
, 6218
41.7%
' 348
 
2.3%
! 27
 
0.2%
" 25
 
0.2%
? 7
 
< 0.1%
· 4
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
j 15
33.3%
a 15
33.3%
c 15
33.3%
Final Punctuation
ValueCountFrequency (%)
53
52.5%
48
47.5%
Initial Punctuation
ValueCountFrequency (%)
47
54.0%
40
46.0%
Open Punctuation
ValueCountFrequency (%)
( 31
51.7%
29
48.3%
Close Punctuation
ValueCountFrequency (%)
) 31
52.5%
28
47.5%
Space Separator
ValueCountFrequency (%)
111952
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 18
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 428793
74.5%
Common 143470
 
24.9%
Latin 3418
 
0.6%
Han 42
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20958
 
4.9%
12766
 
3.0%
12690
 
3.0%
9570
 
2.2%
9454
 
2.2%
9284
 
2.2%
9099
 
2.1%
8726
 
2.0%
8538
 
2.0%
8271
 
1.9%
Other values (786) 319437
74.5%
Han
ValueCountFrequency (%)
4
 
9.5%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (24) 24
57.1%
Common
ValueCountFrequency (%)
111952
78.0%
. 8270
 
5.8%
0 6745
 
4.7%
, 6218
 
4.3%
1 2826
 
2.0%
3 1200
 
0.8%
2 1190
 
0.8%
4 1063
 
0.7%
9 1058
 
0.7%
7 787
 
0.5%
Other values (20) 2161
 
1.5%
Latin
ValueCountFrequency (%)
C 1119
32.7%
A 1118
32.7%
J 1117
32.7%
j 15
 
0.4%
a 15
 
0.4%
c 15
 
0.4%
H 7
 
0.2%
M 7
 
0.2%
S 2
 
0.1%
K 1
 
< 0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428787
74.5%
ASCII 146620
 
25.5%
Punctuation 188
 
< 0.1%
None 79
 
< 0.1%
CJK 41
 
< 0.1%
Compat Jamo 6
 
< 0.1%
Geometric Shapes 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
111952
76.4%
. 8270
 
5.6%
0 6745
 
4.6%
, 6218
 
4.2%
1 2826
 
1.9%
3 1200
 
0.8%
2 1190
 
0.8%
C 1119
 
0.8%
A 1118
 
0.8%
J 1117
 
0.8%
Other values (23) 4865
 
3.3%
Hangul
ValueCountFrequency (%)
20958
 
4.9%
12766
 
3.0%
12690
 
3.0%
9570
 
2.2%
9454
 
2.2%
9284
 
2.2%
9099
 
2.1%
8726
 
2.0%
8538
 
2.0%
8271
 
1.9%
Other values (781) 319431
74.5%
Punctuation
ValueCountFrequency (%)
53
28.2%
48
25.5%
47
25.0%
40
21.3%
None
ValueCountFrequency (%)
29
36.7%
28
35.4%
´ 18
22.8%
· 4
 
5.1%
CJK
ValueCountFrequency (%)
4
 
9.8%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (23) 23
56.1%
Compat Jamo
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Geometric Shapes
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

판결문_원문_제공
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9988 
False
 
12
ValueCountFrequency (%)
True 9988
99.9%
False 12
 
0.1%
2023-12-13T03:17:40.357849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

판결문_번역본_제공
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
True
9952 
False
 
48
ValueCountFrequency (%)
True 9952
99.5%
False 48
 
0.5%
2023-12-13T03:17:40.424330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

생산년도
Real number (ℝ)

Distinct40
Distinct (%)0.4%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1922.4544
Minimum1906
Maximum1945
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:17:40.508673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1906
5-th percentile1910
Q11919
median1919
Q31925
95-th percentile1942
Maximum1945
Range39
Interquartile range (IQR)6

Descriptive statistics

Standard deviation8.2633747
Coefficient of variation (CV)0.0042983463
Kurtosis0.90530311
Mean1922.4544
Median Absolute Deviation (MAD)1
Skewness1.0666081
Sum19216854
Variance68.283361
MonotonicityNot monotonic
2023-12-13T03:17:40.622188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1919 4319
43.2%
1920 1264
 
12.6%
1921 434
 
4.3%
1922 322
 
3.2%
1909 290
 
2.9%
1931 277
 
2.8%
1934 242
 
2.4%
1945 194
 
1.9%
1930 190
 
1.9%
1942 180
 
1.8%
Other values (30) 2284
22.8%
ValueCountFrequency (%)
1906 64
 
0.6%
1907 14
 
0.1%
1908 117
1.2%
1909 290
2.9%
1910 141
1.4%
1911 53
 
0.5%
1912 124
1.2%
1913 80
 
0.8%
1914 2
 
< 0.1%
1915 36
 
0.4%
ValueCountFrequency (%)
1945 194
1.9%
1944 122
1.2%
1943 66
 
0.7%
1942 180
1.8%
1941 88
0.9%
1940 38
 
0.4%
1939 51
 
0.5%
1938 76
 
0.8%
1937 76
 
0.8%
1936 100
1.0%
Distinct817
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:17:40.827047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
Distinct characters13
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

Unique204 ?
Unique (%)2.0%

Sample

1st rowCJA0000477
2nd rowCJA0000408
3rd rowCJA0000131
4th rowCJA0000477
5th rowCJA0001284
ValueCountFrequency (%)
cja0000401 371
 
3.7%
cja0000477 182
 
1.8%
cja0000252 165
 
1.7%
cja0001990 122
 
1.2%
cja0002172 110
 
1.1%
cja0000060 105
 
1.1%
cja0001284 103
 
1.0%
cja0000450 101
 
1.0%
cja0000140 100
 
1.0%
cja0000453 96
 
1.0%
Other values (807) 8545
85.5%
2023-12-13T03:17:41.138111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40562
40.6%
C 10000
 
10.0%
J 10000
 
10.0%
A 10000
 
10.0%
1 5754
 
5.8%
4 5021
 
5.0%
7 3763
 
3.8%
9 3432
 
3.4%
2 3290
 
3.3%
8 2263
 
2.3%
Other values (3) 5915
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70000
70.0%
Uppercase Letter 30000
30.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40562
57.9%
1 5754
 
8.2%
4 5021
 
7.2%
7 3763
 
5.4%
9 3432
 
4.9%
2 3290
 
4.7%
8 2263
 
3.2%
5 2244
 
3.2%
6 2088
 
3.0%
3 1583
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
C 10000
33.3%
J 10000
33.3%
A 10000
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 70000
70.0%
Latin 30000
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40562
57.9%
1 5754
 
8.2%
4 5021
 
7.2%
7 3763
 
5.4%
9 3432
 
4.9%
2 3290
 
4.7%
8 2263
 
3.2%
5 2244
 
3.2%
6 2088
 
3.0%
3 1583
 
2.3%
Latin
ValueCountFrequency (%)
C 10000
33.3%
J 10000
33.3%
A 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40562
40.6%
C 10000
 
10.0%
J 10000
 
10.0%
A 10000
 
10.0%
1 5754
 
5.8%
4 5021
 
5.0%
7 3763
 
3.8%
9 3432
 
3.4%
2 3290
 
3.3%
8 2263
 
2.3%
Other values (3) 5915
 
5.9%

마이크로필름번호
Real number (ℝ)

SKEWED 

Distinct566
Distinct (%)5.7%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean938613.8
Minimum95375
Maximum9671011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:17:41.271307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95375
5-th percentile930585
Q1930673
median930897
Q3950065
95-th percentile960846
Maximum9671011
Range9575636
Interquartile range (IQR)19392

Descriptive statistics

Standard deviation129692.42
Coefficient of variation (CV)0.13817442
Kurtosis4115.2947
Mean938613.8
Median Absolute Deviation (MAD)228
Skewness60.537492
Sum9.3833221 × 109
Variance1.6820123 × 1010
MonotonicityNot monotonic
2023-12-13T03:17:41.416756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
930909 375
 
3.8%
930675 198
 
2.0%
930679 195
 
1.9%
930586 175
 
1.8%
930908 169
 
1.7%
930673 168
 
1.7%
930900 158
 
1.6%
950039 156
 
1.6%
930676 149
 
1.5%
930670 149
 
1.5%
Other values (556) 8105
81.0%
ValueCountFrequency (%)
95375 20
 
0.2%
930530 13
 
0.1%
930531 12
 
0.1%
930550 85
0.9%
930552 5
 
0.1%
930553 12
 
0.1%
930554 3
 
< 0.1%
930558 1
 
< 0.1%
930560 62
0.6%
930565 2
 
< 0.1%
ValueCountFrequency (%)
9671011 2
 
< 0.1%
970977 2
 
< 0.1%
970976 1
 
< 0.1%
961012 1
 
< 0.1%
961011 1
 
< 0.1%
960992 3
 
< 0.1%
960991 1
 
< 0.1%
960989 4
 
< 0.1%
960987 23
0.2%
960979 5
 
0.1%

Interactions

2023-12-13T03:17:33.545643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:32.861515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.221161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.653604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:32.979590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.338394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.764751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.106379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:17:33.446370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:17:41.498160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번판결문_원문_제공판결문_번역본_제공생산년도마이크로필름번호
연번1.0000.0190.0200.2210.000
판결문_원문_제공0.0191.0000.5260.0730.000
판결문_번역본_제공0.0200.5261.0000.1100.000
생산년도0.2210.0730.1101.0000.065
마이크로필름번호0.0000.0000.0000.0651.000
2023-12-13T03:17:41.597901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판결문_원문_제공판결문_번역본_제공
판결문_원문_제공1.0000.353
판결문_번역본_제공0.3531.000
2023-12-13T03:17:41.679541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번생산년도마이크로필름번호판결문_원문_제공판결문_번역본_제공
연번1.000-0.014-0.0560.0140.015
생산년도-0.0141.0000.2630.0560.081
마이크로필름번호-0.0560.2631.0000.0000.000
판결문_원문_제공0.0140.0560.0001.0000.353
판결문_번역본_제공0.0150.0810.0000.3531.000

Missing values

2023-12-13T03:17:33.906077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:17:34.099293image/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.
2023-12-13T03:17:34.260979image/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

연번이름_별명당시나이본적주소죄명주문판결날짜사건개요판결문_원문_제공판결문_번역본_제공생산년도관리번호마이크로필름번호
37933794김응하(金應河)63세황해도 수안군 수안면 석교리내란관할재판소를 경성지방법원으로 지정1920-03-22 오전 12:00:00천도교도들이 독립선언서를 인쇄배포하고 군중이 시위하며 헌병분대내로 난입 하자 발포저지하였다.YY1920CJA0000477930679
1774817749최종하(崔宗河)43세강원도 횡성군 횡성면 읍상리보안법위반징역 6월1919-06-09 오전 12:00:00조선 독립선언서 12장을 교부받아 신재근, 김인경에게 취지를 말하고 교부하였다.YY1919CJA0000408930903
1548615487정봉조(鄭鳳朝)31세지나 간도 장백현 16도구 서덕수대정8년 제령 제7호 위반, 폭발물취체벌칙위반, 강도살인, 상인방조, 불법체포, 감금, 상해징역 10년1924-03-24 오전 12:00:00지나에서 광정단을 조직하고 조선독립운도에 종사하여 광정단원 40여명이 군자금및 무기약탈을 목적으로 조선 내로 침입하고 영성경찰관주재소를 습격하여 순사를 살해하고 다른 2명의 순사에게 중상을 입히는 사건을 방조, 밀정자를 감금, 구타하였다.YY1924CJA0000131930609
1377013771이채룡(李彩龍)40세황해도 수안군 수안면 자의리내란관할재판소를 경성지방법원으로 지정1920-03-22 오전 12:00:00천도교도들이 독립선언서를 인쇄배포하고 군중이 시위하며 헌병분대내로 난입 하자 발포저지하였다.YY1920CJA0000477930679
1364713648이중식(李仲植)40세경북 영덕군 영해면 묘곡동소요, 공무집행방해, 건조물손괴, 기물손괴, 공문서훼기, 상해, 보안법위반징역 6월1919-06-05 오전 12:00:00성내동에서 이천여명의 군중과 같이 한국독립만세를 부르고 시장 부근을 행진하였다.YY1919CJA0001284950039
42614262김종창(金鍾暢)41세전라북도 임실군 둔남면 둔덕리소요징역 1년1919-07-31 오전 12:00:001919년 3월 23일 오수리 장날 수괴 이기송은 연설하고 군중을 지휘 만세를 고창하며 소요 시위 관공서를 파괴하였다.YY1919CJA0001749960864
1649416495좌공림(左公琳)29세경성부 화동 98번지치안유지법위반징역 2년1929-03-22 오전 12:00:00공산당이 조선이 일본의 압제에서 벗어나 공산사회를 실현하는 것이 목적인 줄 알면서 가입하여 활동하였다.YY1929CJA0000398930942
58925893문영복(文永福)25세전라남도 영암군 영암면 장암리 569 번지가택침입, 폭력행위 등 처벌에 관한 법률위반벌금 30원 환형유치일수 30일1933-09-29 오전 12:00:00<NA>YY1934CJA0002027960659
76787679변길성(卞吉成)22세전라남도 나주군 봉황면 덕림리대정8년 제령 제7호 위반무죄1921-08-13 오전 12:00:00덕림 부속학교의 교사로 조선의 독립사상을 고취시키기 위하여 생도에게 가르칠 목적으로 감동가 노래를 복사했다.YY1921CJA0001955960597
1345413455이종기(李鍾基)25세경상북도 의성군 단촌면 병방동 472번지대정8년 제령 제7호 위반원판결취소 징역 1년1921-11-26 오전 12:00:00치성비를 출자하고 일대집단을 조직하여 국권회복운동을 결의하여 교주 차경석이1924년 갑자년에 계룡산에 도읍을 정하고 제위에 올라 독립조선을 통치할 것이라고 망상하고 선전하였다.YY1922CJA0002172950216
연번이름_별명당시나이본적주소죄명주문판결날짜사건개요판결문_원문_제공판결문_번역본_제공생산년도관리번호마이크로필름번호
1207812079이병국(李炳國)23세경성부 도렴동 52 번지치안유지법위반징역 1년6월집행유예 2년1934-09-17 오전 12:00:00사유재산제도를 부인하고 공산주의 제도 사회실현을 목적으로 좌익서적을 탐독하고 연구하였으며 비밀결사를 조직하여 활동하였다.YY1934CJA0001799960905
1729317294최봉규(崔鳳奎)20세(5월 25일생)함흥부 주길정 67번지치안유지법위반징역 2년 원심미결구류일수 중 60일 당심미결구류일수 중 60일 본형에 산입1936-03-06 오전 12:00:00메이데이를 기념하며 사유재산제도를 부인하고 공산주의 연구 그룹을 조직하는 등 체제개혁을 목적으로 하는 공산주의 실천운동을 하였다.YY1936CJA0000649930635
1072810729유창성(柳昌成)44세전라북도 완주군 소양면 화심리 514 번지육해군형법위반, 조선임시보안령위반징역 1년1942-11-27 오전 12:00:00조선인 경제범을 검거 다액의 벌금을 징수하여 전비로 쓰고 있고 전쟁이 끝나면 벌금을 반환해야 한다고 말하였다.YY1942CJA0001815960923
55975598덕본광의(德本光毅)한관영(韓寬泳)26세경성부 중구 남미창정 62번지치안유지법위반경성지방법원 합의부의 공판에 부침1943-10-25 오전 12:00:00좌익서적을 탐독 공산주의사상에 공명하여 조선의 독립과 공산화를 희망하고 경성콤그룹의 목적수행을 위해 활동하였다.YY1945CJA0000008930974
1550815509정석규(鄭錫奎)19세전라남도 광주군 광주면 서남리 최동문(崔東文)방치안유지법위반징역 2년6월 미결구류일수 70일 본형에 산입1930-10-18 오전 12:00:00<NA>YY1931CJA0001990960623
31203121김영기(金寧基)36세경상북도 김천군 대항면 향천동대정8년 제령 제7호 위반상고 기각1920-04-17 오전 12:00:00CJA0000750, CJA0000752의 관련건YY1920CJA0000478930679
1159611597이기영(李璣榮)이무록(李武菉)40세충청북도 영동군 학산면 봉소리보안법위반, 소요공소 기각1919-09-17 오전 12:00:00조선독립만세운동을 찬성하여 독립시위운동을 하였다.YY1919CJA0000140930586
36753676김윤옥(金允玉)18세(1월 12일생)황해도 송화군 연정면 조령리 284번지출판법위반, 보안법위반경성지방법원의 공판에 부침1919-08-30 오전 12:00:00조선독립선언과 동시에 선언서를 발포하여 대한독립만세, 조선독립만세를 절구하며 독립시위운동을 하였다.YY1920CJA0000401930909
36253626김윤구(金崙求)27세경기도 양평군 용문면 오촌리 281번지보안법위반상고 기각1919-07-26 오전 12:00:00<NA>YY1919CJA0000418930900
21132114김명진(金明辰)18세(10월 8일생)인천부 내리 152번지보안법위반, 절도, 전신법위반상고 기각1919-10-09 오전 12:00:00CJA0000142, CJA0000418 관련건YY1919CJA0000678930676