Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Numeric1
Categorical1
Text2
DateTime1

Dataset

Description국가기록원에서 보유하고 있는 관보 컬렉션 기본정보(관보ID, 관보유형(시대별), 기록물철ID, 관보호수)
Author행정안전부 국가기록원
URLhttps://www.data.go.kr/data/15049392/fileData.do

Alerts

순번 is highly overall correlated with 관보유형High correlation
관보유형 is highly overall correlated with 순번High correlation
관보유형 is highly imbalanced (50.3%)Imbalance
순번 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:07:39.661026
Analysis finished2023-12-12 03:07:40.953443
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13377.372
Minimum2
Maximum26992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:07:41.051322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1270.85
Q16658.75
median13303.5
Q320137.25
95-th percentile25680.05
Maximum26992
Range26990
Interquartile range (IQR)13478.5

Descriptive statistics

Standard deviation7803.246
Coefficient of variation (CV)0.58331682
Kurtosis-1.1965546
Mean13377.372
Median Absolute Deviation (MAD)6753
Skewness0.017961548
Sum1.3377372 × 108
Variance60890649
MonotonicityNot monotonic
2023-12-12T12:07:41.249777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11657 1
 
< 0.1%
16101 1
 
< 0.1%
2049 1
 
< 0.1%
13308 1
 
< 0.1%
2696 1
 
< 0.1%
1856 1
 
< 0.1%
18496 1
 
< 0.1%
20178 1
 
< 0.1%
7322 1
 
< 0.1%
15004 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
9 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
ValueCountFrequency (%)
26992 1
< 0.1%
26991 1
< 0.1%
26986 1
< 0.1%
26983 1
< 0.1%
26981 1
< 0.1%
26980 1
< 0.1%
26974 1
< 0.1%
26972 1
< 0.1%
26971 1
< 0.1%
26970 1
< 0.1%

관보유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
관보
5706 
조선총독부관보
3795 
조달관보
 
249
미군정관보
 
188
관보2
 
36

Length

Max length7
Median length2
Mean length4.0125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관보
2nd row관보
3rd row조선총독부관보
4th row조달관보
5th row조선총독부관보

Common Values

ValueCountFrequency (%)
관보 5706
57.1%
조선총독부관보 3795
38.0%
조달관보 249
 
2.5%
미군정관보 188
 
1.9%
관보2 36
 
0.4%
월간목록 26
 
0.3%

Length

2023-12-12T12:07:41.453340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:07:41.628318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관보 5706
57.1%
조선총독부관보 3795
38.0%
조달관보 249
 
2.5%
미군정관보 188
 
1.9%
관보2 36
 
0.4%
월간목록 26
 
0.3%
Distinct9990
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:07:42.023356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length21.0408
Min length2

Characters and Unicode

Total characters210408
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9981 ?
Unique (%)99.8%

Sample

1st row관보제12884호(1994.12.7)
2nd row관보제11675호(1990년11월16일)
3rd row조선총독부 관보(1940년 04월 13)
4th row조달관보제14499호(2000.5.9)
5th row조선총독부 관보(1936년 11월 25)
ValueCountFrequency (%)
조선총독부 3795
 
15.8%
관보 748
 
3.1%
12월 389
 
1.6%
05월 369
 
1.5%
10월 361
 
1.5%
11월 360
 
1.5%
07월 355
 
1.5%
08월 345
 
1.4%
03월 336
 
1.4%
06월 327
 
1.4%
Other values (6113) 16565
69.2%
2023-12-12T12:07:42.698020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25077
 
11.9%
9 15802
 
7.5%
13952
 
6.6%
2 11021
 
5.2%
) 10130
 
4.8%
( 10130
 
4.8%
10003
 
4.8%
10000
 
4.8%
0 9953
 
4.7%
8819
 
4.2%
Other values (58) 85521
40.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99068
47.1%
Other Letter 74780
35.5%
Space Separator 13952
 
6.6%
Close Punctuation 10132
 
4.8%
Open Punctuation 10131
 
4.8%
Other Punctuation 2343
 
1.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10003
13.4%
10000
13.4%
8819
11.8%
8819
11.8%
5982
8.0%
5877
7.9%
4998
6.7%
4044
5.4%
3795
 
5.1%
3795
 
5.1%
Other values (40) 8648
11.6%
Decimal Number
ValueCountFrequency (%)
1 25077
25.3%
9 15802
16.0%
2 11021
11.1%
0 9953
 
10.0%
3 6871
 
6.9%
4 6396
 
6.5%
7 6137
 
6.2%
8 6081
 
6.1%
6 5928
 
6.0%
5 5802
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 10130
> 99.9%
] 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 10130
> 99.9%
[ 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 2342
> 99.9%
, 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
13952
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 135628
64.5%
Hangul 74780
35.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10003
13.4%
10000
13.4%
8819
11.8%
8819
11.8%
5982
8.0%
5877
7.9%
4998
6.7%
4044
5.4%
3795
 
5.1%
3795
 
5.1%
Other values (40) 8648
11.6%
Common
ValueCountFrequency (%)
1 25077
18.5%
9 15802
11.7%
13952
10.3%
2 11021
8.1%
) 10130
7.5%
( 10130
7.5%
0 9953
 
7.3%
3 6871
 
5.1%
4 6396
 
4.7%
7 6137
 
4.5%
Other values (8) 20159
14.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135628
64.5%
Hangul 74780
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25077
18.5%
9 15802
11.7%
13952
10.3%
2 11021
8.1%
) 10130
7.5%
( 10130
7.5%
0 9953
 
7.3%
3 6871
 
5.1%
4 6396
 
4.7%
7 6137
 
4.5%
Other values (8) 20159
14.9%
Hangul
ValueCountFrequency (%)
10003
13.4%
10000
13.4%
8819
11.8%
8819
11.8%
5982
8.0%
5877
7.9%
4998
6.7%
4044
5.4%
3795
 
5.1%
3795
 
5.1%
Other values (40) 8648
11.6%
Distinct9857
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1910-09-03 00:00:00
Maximum2004-10-20 00:00:00
2023-12-12T12:07:42.902765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:07:43.088272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:07:43.510886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st rowBA0426937
2nd rowBA0197654
3rd rowJ19400413
4th rowBA0589647
5th rowJ19361125
ValueCountFrequency (%)
ba0426937 1
 
< 0.1%
j19330703 1
 
< 0.1%
j19431217 1
 
< 0.1%
ba0192925 1
 
< 0.1%
ba0185956 1
 
< 0.1%
ba0752093 1
 
< 0.1%
ba0188621 1
 
< 0.1%
ba0186195 1
 
< 0.1%
j19381215 1
 
< 0.1%
194710154 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T12:07:44.158977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15832
17.6%
0 13528
15.0%
9 10449
11.6%
2 7069
7.9%
B 6017
 
6.7%
A 6017
 
6.7%
8 5663
 
6.3%
4 4768
 
5.3%
3 4664
 
5.2%
5 4346
 
4.8%
Other values (3) 11647
12.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74171
82.4%
Uppercase Letter 15829
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15832
21.3%
0 13528
18.2%
9 10449
14.1%
2 7069
9.5%
8 5663
 
7.6%
4 4768
 
6.4%
3 4664
 
6.3%
5 4346
 
5.9%
7 4324
 
5.8%
6 3528
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 6017
38.0%
A 6017
38.0%
J 3795
24.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74171
82.4%
Latin 15829
 
17.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15832
21.3%
0 13528
18.2%
9 10449
14.1%
2 7069
9.5%
8 5663
 
7.6%
4 4768
 
6.4%
3 4664
 
6.3%
5 4346
 
5.9%
7 4324
 
5.8%
6 3528
 
4.8%
Latin
ValueCountFrequency (%)
B 6017
38.0%
A 6017
38.0%
J 3795
24.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15832
17.6%
0 13528
15.0%
9 10449
11.6%
2 7069
7.9%
B 6017
 
6.7%
A 6017
 
6.7%
8 5663
 
6.3%
4 4768
 
5.3%
3 4664
 
5.2%
5 4346
 
4.8%
Other values (3) 11647
12.9%

Interactions

2023-12-12T12:07:40.597038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:07:44.317047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번관보유형
순번1.0000.750
관보유형0.7501.000
2023-12-12T12:07:44.439546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번관보유형
순번1.0000.521
관보유형0.5211.000

Missing values

2023-12-12T12:07:40.767220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:07:40.885568image/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

순번관보유형관보명발행날짜관리번호
1165611657관보관보제12884호(1994.12.7)1994-12-07BA0426937
1042410425관보관보제11675호(1990년11월16일)1990-11-16BA0197654
1809818099조선총독부관보조선총독부 관보(1940년 04월 13)1940-04-13J19400413
1567415675조달관보조달관보제14499호(2000.5.9)2000-05-09BA0589647
1915819159조선총독부관보조선총독부 관보(1936년 11월 25)1936-11-25J19361125
94859486관보관보제10588호(1987년3월18일)1987-03-18BA0196556
2689026891조선총독부관보조선총독부 관보(1910년 12월 14)1910-12-14J19101214
1881818819조선총독부관보조선총독부 관보(1937년 11월 25)1937-11-25J19371125
2136521366조선총독부관보조선총독부 관보(1929년 05월 21)1929-05-21J19290521
1038410385관보관보제11630호(1990년9월19일)1990-09-19BA0197608
순번관보유형관보명발행날짜관리번호
2516625167조선총독부관보조선총독부 관보(1916년 09월 08)1916-09-08J19160908
65466547관보관보제7224호(1975년12월16일)1975-12-16BA0193181
1600616007조달관보조달관보제14444호(2000.3.2)2000-03-02BA0589600
1948919490조선총독부관보조선총독부 관보(1935년 11월 16)1935-11-16J19351116
289290관보관보 제377호(1950년 6월 17일)1950-06-17BA0158826
1280212803관보관보제14209호(1999.5.21)1999-05-21BA0588601
63126313관보관보제6965호(1975년2월4일)1975-02-04BA0192922
2484424845조선총독부관보조선총독부 관보(1917년 10월 02)1917-10-02J19171002
2620626207조선총독부관보조선총독부 관보(1913년 05월 13)1913-05-13J19130513
2581125812조선총독부관보조선총독부 관보(1914년 08월 03)1914-08-03J19140803