Overview

Dataset statistics

Number of variables12
Number of observations1639
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory163.4 KiB
Average record size in memory102.1 B

Variable types

Text3
Numeric6
Categorical3

Dataset

Description경상남도기록원이 소장하고 있는 비전자기록물 중 스캐닝을 완료하여 원문 디지털화가 완료된 기록물 목록을 게시합니다.
URLhttps://www.data.go.kr/data/15084203/fileData.do

Alerts

처리과기관코드 is highly overall correlated with 업로드기관High correlation
생산년도 is highly overall correlated with 업로드기관High correlation
쪽수 is highly overall correlated with 이미지수량High correlation
이미지수량 is highly overall correlated with 쪽수High correlation
업로드기관 is highly overall correlated with 처리과기관코드 and 1 other fieldsHigh correlation
기록물형태 is highly imbalanced (98.1%)Imbalance
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:04:17.865726
Analysis finished2023-12-12 07:04:23.531934
Duration5.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct1639
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-12-12T16:04:23.792017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.177547
Min length9

Characters and Unicode

Total characters19959
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1639 ?
Unique (%)100.0%

Sample

1st rowGA0016293
2nd rowGA0016294
3rd rowGA0016295-001
4th rowGA0016295-002
5th rowGA0016296
ValueCountFrequency (%)
ga0016293 1
 
0.1%
ga0016979-001 1
 
0.1%
ga0016987 1
 
0.1%
ga0016986-002 1
 
0.1%
ga0016986-001 1
 
0.1%
ga0016985 1
 
0.1%
ga0016984 1
 
0.1%
ga0016983 1
 
0.1%
ga0016982 1
 
0.1%
ga0016981 1
 
0.1%
Other values (1629) 1629
99.4%
2023-12-12T16:04:24.355655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6274
31.4%
1 2526
12.7%
6 1723
 
8.6%
G 1639
 
8.2%
A 1636
 
8.2%
- 1302
 
6.5%
2 945
 
4.7%
7 818
 
4.1%
9 765
 
3.8%
3 737
 
3.7%
Other values (4) 1594
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15379
77.1%
Uppercase Letter 3278
 
16.4%
Dash Punctuation 1302
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6274
40.8%
1 2526
16.4%
6 1723
 
11.2%
2 945
 
6.1%
7 818
 
5.3%
9 765
 
5.0%
3 737
 
4.8%
4 652
 
4.2%
8 471
 
3.1%
5 468
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
G 1639
50.0%
A 1636
49.9%
B 3
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16681
83.6%
Latin 3278
 
16.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6274
37.6%
1 2526
15.1%
6 1723
 
10.3%
- 1302
 
7.8%
2 945
 
5.7%
7 818
 
4.9%
9 765
 
4.6%
3 737
 
4.4%
4 652
 
3.9%
8 471
 
2.8%
Latin
ValueCountFrequency (%)
G 1639
50.0%
A 1636
49.9%
B 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19959
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6274
31.4%
1 2526
12.7%
6 1723
 
8.6%
G 1639
 
8.2%
A 1636
 
8.2%
- 1302
 
6.5%
2 945
 
4.7%
7 818
 
4.1%
9 765
 
3.8%
3 737
 
3.7%
Other values (4) 1594
 
8.0%

처리과기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7062969.7
Minimum5340018
Maximum9932530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:24.587143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5340018
5-th percentile6480030
Q16480966
median6480966
Q36480978
95-th percentile9932493
Maximum9932530
Range4592512
Interquartile range (IQR)12

Descriptive statistics

Standard deviation1349626.5
Coefficient of variation (CV)0.19108485
Kurtosis0.75233207
Mean7062969.7
Median Absolute Deviation (MAD)10
Skewness1.5910605
Sum1.1576207 × 1010
Variance1.8214917 × 1012
MonotonicityNot monotonic
2023-12-12T16:04:24.779607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6480966 685
41.8%
9931588 95
 
5.8%
9932493 94
 
5.7%
6480064 81
 
4.9%
6480975 78
 
4.8%
6480978 69
 
4.2%
6481118 61
 
3.7%
6480912 50
 
3.1%
9932419 48
 
2.9%
6480855 46
 
2.8%
Other values (43) 332
20.3%
ValueCountFrequency (%)
5340018 11
 
0.7%
5340075 2
 
0.1%
5340085 28
1.7%
5340091 6
 
0.4%
6480000 22
1.3%
6480004 2
 
0.1%
6480013 3
 
0.2%
6480030 22
1.3%
6480032 3
 
0.2%
6480038 5
 
0.3%
ValueCountFrequency (%)
9932530 1
 
0.1%
9932527 2
 
0.1%
9932506 1
 
0.1%
9932496 3
 
0.2%
9932493 94
5.7%
9932459 1
 
0.1%
9932455 3
 
0.2%
9932419 48
2.9%
9932008 19
 
1.2%
9931591 3
 
0.2%

구기록물생산기관명
Text

Distinct53
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-12-12T16:04:25.034300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length13.269067
Min length4

Characters and Unicode

Total characters21748
Distinct characters108
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

Unique9 ?
Unique (%)0.5%

Sample

1st row경상남도
2nd row경상남도
3rd row경상남도
4th row경상남도
5th row경상남도
ValueCountFrequency (%)
경상남도 1636
36.3%
농정국 694
15.4%
농업정책과 685
15.2%
농업기술원 125
 
2.8%
도시교통국 112
 
2.5%
사천군 101
 
2.2%
삼천포시 95
 
2.1%
총무과 84
 
1.9%
환경산림국 82
 
1.8%
산림녹지과 78
 
1.7%
Other values (62) 819
18.2%
2023-12-12T16:04:25.431319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2872
13.2%
경 1803
 
8.3%
도 1790
 
8.2%
상 1642
 
7.6%
남 1639
 
7.5%
정 1628
 
7.5%
농 1535
 
7.1%
과 1201
 
5.5%
국 1052
 
4.8%
업 918
 
4.2%
Other values (98) 5668
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18876
86.8%
Space Separator 2872
 
13.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1803
 
9.6%
도 1790
 
9.5%
상 1642
 
8.7%
남 1639
 
8.7%
정 1628
 
8.6%
농 1535
 
8.1%
과 1201
 
6.4%
국 1052
 
5.6%
업 918
 
4.9%
책 869
 
4.6%
Other values (97) 4799
25.4%
Space Separator
ValueCountFrequency (%)
2872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18876
86.8%
Common 2872
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1803
 
9.6%
도 1790
 
9.5%
상 1642
 
8.7%
남 1639
 
8.7%
정 1628
 
8.6%
농 1535
 
8.1%
과 1201
 
6.4%
국 1052
 
5.6%
업 918
 
4.9%
책 869
 
4.6%
Other values (97) 4799
25.4%
Common
ValueCountFrequency (%)
2872
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18876
86.8%
ASCII 2872
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2872
100.0%
Hangul
ValueCountFrequency (%)
경 1803
 
9.6%
도 1790
 
9.5%
상 1642
 
8.7%
남 1639
 
8.7%
정 1628
 
8.6%
농 1535
 
8.1%
과 1201
 
6.4%
국 1052
 
5.6%
업 918
 
4.9%
책 869
 
4.6%
Other values (97) 4799
25.4%

업로드기관
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
경상남도
1341 
사천시
246 
거제군
 
52

Length

Max length4
Median length4
Mean length3.8181818
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 1341
81.8%
사천시 246
 
15.0%
거제군 52
 
3.2%

Length

2023-12-12T16:04:25.598338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:04:25.722441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 1341
81.8%
사천시 246
 
15.0%
거제군 52
 
3.2%

생산년도
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1967.2459
Minimum1947
Maximum1998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:25.848261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1947
5-th percentile1950
Q11955
median1969
Q31978
95-th percentile1981
Maximum1998
Range51
Interquartile range (IQR)23

Descriptive statistics

Standard deviation11.31786
Coefficient of variation (CV)0.0057531498
Kurtosis-1.42086
Mean1967.2459
Median Absolute Deviation (MAD)10
Skewness-0.080865637
Sum3224316
Variance128.09396
MonotonicityNot monotonic
2023-12-12T16:04:26.008442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1953 232
14.2%
1978 171
 
10.4%
1980 118
 
7.2%
1979 104
 
6.3%
1950 95
 
5.8%
1977 88
 
5.4%
1975 82
 
5.0%
1958 65
 
4.0%
1955 59
 
3.6%
1960 57
 
3.5%
Other values (30) 568
34.7%
ValueCountFrequency (%)
1947 2
 
0.1%
1950 95
5.8%
1952 10
 
0.6%
1953 232
14.2%
1954 17
 
1.0%
1955 59
 
3.6%
1956 21
 
1.3%
1957 16
 
1.0%
1958 65
 
4.0%
1959 56
 
3.4%
ValueCountFrequency (%)
1998 3
 
0.2%
1992 2
 
0.1%
1991 11
 
0.7%
1990 1
 
0.1%
1989 2
 
0.1%
1986 9
 
0.5%
1983 12
 
0.7%
1982 12
 
0.7%
1981 39
 
2.4%
1980 118
7.2%

권호수
Real number (ℝ)

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7352044
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:26.124591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.90483665
Coefficient of variation (CV)0.52145825
Kurtosis1.2230646
Mean1.7352044
Median Absolute Deviation (MAD)0
Skewness1.2044507
Sum2844
Variance0.81872937
MonotonicityNot monotonic
2023-12-12T16:04:26.225947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 834
50.9%
2 497
30.3%
3 232
 
14.2%
4 63
 
3.8%
5 10
 
0.6%
6 3
 
0.2%
ValueCountFrequency (%)
1 834
50.9%
2 497
30.3%
3 232
 
14.2%
4 63
 
3.8%
5 10
 
0.6%
6 3
 
0.2%
ValueCountFrequency (%)
6 3
 
0.2%
5 10
 
0.6%
4 63
 
3.8%
3 232
 
14.2%
2 497
30.3%
1 834
50.9%

서비스철제목
Text

Distinct1359
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-12-12T16:04:26.549326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length35
Mean length17.71507
Min length2

Characters and Unicode

Total characters29035
Distinct characters306
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1222 ?
Unique (%)74.6%

Sample

1st row사령원부
2nd row농기업화촉진자금
3rd row자가용전기공작물허가업체대장(2-1)
4th row자가용전기공작물허가업체대장(2-2)
5th row직제.정원
ValueCountFrequency (%)
27213 363
 
11.2%
농지상환대장(하동군 185
 
5.7%
22681 122
 
3.8%
토지이동관계철(하동군 48
 
1.5%
학적부 37
 
1.1%
분배농지상환대장 32
 
1.0%
예정지 26
 
0.8%
78절대농지 25
 
0.8%
농촌진흥원 24
 
0.7%
신축공사 23
 
0.7%
Other values (1428) 2356
72.7%
2023-12-12T16:04:27.081595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2232
 
7.7%
( 2190
 
7.5%
) 2188
 
7.5%
1603
 
5.5%
- 1463
 
5.0%
1 1267
 
4.4%
3 1249
 
4.3%
지 845
 
2.9%
대 745
 
2.6%
군 668
 
2.3%
Other values (296) 14585
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14838
51.1%
Decimal Number 6575
22.6%
Open Punctuation 2190
 
7.5%
Close Punctuation 2188
 
7.5%
Space Separator 1603
 
5.5%
Dash Punctuation 1463
 
5.0%
Other Punctuation 149
 
0.5%
Math Symbol 9
 
< 0.1%
Modifier Symbol 8
 
< 0.1%
Uppercase Letter 5
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 845
 
5.7%
대 745
 
5.0%
군 668
 
4.5%
장 642
 
4.3%
동 584
 
3.9%
상 561
 
3.8%
농 561
 
3.8%
하 485
 
3.3%
환 464
 
3.1%
계 343
 
2.3%
Other values (268) 8940
60.3%
Decimal Number
ValueCountFrequency (%)
2 2232
33.9%
1 1267
19.3%
3 1249
19.0%
7 588
 
8.9%
4 380
 
5.8%
8 270
 
4.1%
6 262
 
4.0%
5 149
 
2.3%
0 99
 
1.5%
9 79
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
P 1
20.0%
K 1
20.0%
I 1
20.0%
L 1
20.0%
E 1
20.0%
Other Punctuation
ValueCountFrequency (%)
* 65
43.6%
. 35
23.5%
, 29
19.5%
/ 20
 
13.4%
Open Punctuation
ValueCountFrequency (%)
( 2190
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2188
100.0%
Space Separator
ValueCountFrequency (%)
1603
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1463
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 8
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14837
51.1%
Common 14185
48.9%
Latin 10
 
< 0.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 845
 
5.7%
대 745
 
5.0%
군 668
 
4.5%
장 642
 
4.3%
동 584
 
3.9%
상 561
 
3.8%
농 561
 
3.8%
하 485
 
3.3%
환 464
 
3.1%
계 343
 
2.3%
Other values (268) 8939
60.2%
Common
ValueCountFrequency (%)
2 2232
15.7%
( 2190
15.4%
) 2188
15.4%
1603
11.3%
- 1463
10.3%
1 1267
8.9%
3 1249
8.8%
7 588
 
4.1%
4 380
 
2.7%
8 270
 
1.9%
Other values (10) 755
 
5.3%
Latin
ValueCountFrequency (%)
Ⅱ 4
40.0%
P 1
 
10.0%
w 1
 
10.0%
K 1
 
10.0%
I 1
 
10.0%
L 1
 
10.0%
E 1
 
10.0%
Han
ValueCountFrequency (%)
一 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14835
51.1%
ASCII 14191
48.9%
Number Forms 4
 
< 0.1%
CJK 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2232
15.7%
( 2190
15.4%
) 2188
15.4%
1603
11.3%
- 1463
10.3%
1 1267
8.9%
3 1249
8.8%
7 588
 
4.1%
4 380
 
2.7%
8 270
 
1.9%
Other values (16) 761
 
5.4%
Hangul
ValueCountFrequency (%)
지 845
 
5.7%
대 745
 
5.0%
군 668
 
4.5%
장 642
 
4.3%
동 584
 
3.9%
상 561
 
3.8%
농 561
 
3.8%
하 485
 
3.3%
환 464
 
3.1%
계 343
 
2.3%
Other values (267) 8937
60.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
100.0%
CJK
ValueCountFrequency (%)
一 3
100.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

기록물형태
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
일반문서
1636 
도면
 
3

Length

Max length4
Median length4
Mean length3.9963392
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반문서 1636
99.8%
도면 3
 
0.2%

Length

2023-12-12T16:04:27.240570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:04:27.348929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반문서 1636
99.8%
도면 3
 
0.2%

보존기간
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
영구
963 
준영구
529 
30년
147 

Length

Max length3
Median length2
Mean length2.4124466
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영구
2nd row영구
3rd row준영구
4th row준영구
5th row준영구

Common Values

ValueCountFrequency (%)
영구 963
58.8%
준영구 529
32.3%
30년 147
 
9.0%

Length

2023-12-12T16:04:27.452516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:04:27.566101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영구 963
58.8%
준영구 529
32.3%
30년 147
 
9.0%

건수
Real number (ℝ)

Distinct63
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1012813
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:27.710916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile20.1
Maximum84
Range83
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.8860167
Coefficient of variation (CV)2.4104703
Kurtosis23.653004
Mean4.1012813
Median Absolute Deviation (MAD)0
Skewness4.5608977
Sum6722
Variance97.733326
MonotonicityNot monotonic
2023-12-12T16:04:27.879138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1305
79.6%
2 38
 
2.3%
3 28
 
1.7%
5 21
 
1.3%
7 20
 
1.2%
6 17
 
1.0%
9 17
 
1.0%
4 14
 
0.9%
8 14
 
0.9%
13 13
 
0.8%
Other values (53) 152
 
9.3%
ValueCountFrequency (%)
1 1305
79.6%
2 38
 
2.3%
3 28
 
1.7%
4 14
 
0.9%
5 21
 
1.3%
6 17
 
1.0%
7 20
 
1.2%
8 14
 
0.9%
9 17
 
1.0%
10 11
 
0.7%
ValueCountFrequency (%)
84 1
0.1%
81 1
0.1%
80 1
0.1%
77 1
0.1%
73 1
0.1%
71 1
0.1%
70 1
0.1%
69 1
0.1%
68 2
0.1%
66 1
0.1%

쪽수
Real number (ℝ)

HIGH CORRELATION 

Distinct408
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.42831
Minimum2
Maximum616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:28.071972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile44
Q1124
median163
Q3218
95-th percentile387.1
Maximum616
Range614
Interquartile range (IQR)94

Descriptive statistics

Standard deviation100.36353
Coefficient of variation (CV)0.54715395
Kurtosis2.0223651
Mean183.42831
Median Absolute Deviation (MAD)44
Skewness1.2097605
Sum300639
Variance10072.837
MonotonicityNot monotonic
2023-12-12T16:04:28.268713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144 19
 
1.2%
136 18
 
1.1%
172 17
 
1.0%
126 17
 
1.0%
129 15
 
0.9%
170 15
 
0.9%
186 15
 
0.9%
130 15
 
0.9%
158 15
 
0.9%
150 15
 
0.9%
Other values (398) 1478
90.2%
ValueCountFrequency (%)
2 1
 
0.1%
3 1
 
0.1%
5 2
0.1%
7 1
 
0.1%
8 3
0.2%
9 4
0.2%
10 3
0.2%
11 1
 
0.1%
12 3
0.2%
13 3
0.2%
ValueCountFrequency (%)
616 1
0.1%
615 1
0.1%
602 1
0.1%
590 1
0.1%
585 1
0.1%
582 1
0.1%
568 1
0.1%
555 1
0.1%
548 1
0.1%
546 2
0.1%

이미지수량
Real number (ℝ)

HIGH CORRELATION 

Distinct408
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183.43624
Minimum2
Maximum616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2023-12-12T16:04:28.440808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile44
Q1124
median163
Q3218
95-th percentile387.1
Maximum616
Range614
Interquartile range (IQR)94

Descriptive statistics

Standard deviation100.36192
Coefficient of variation (CV)0.54712157
Kurtosis2.0222718
Mean183.43624
Median Absolute Deviation (MAD)44
Skewness1.2096108
Sum300652
Variance10072.516
MonotonicityNot monotonic
2023-12-12T16:04:28.623991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144 19
 
1.2%
136 18
 
1.1%
172 17
 
1.0%
126 16
 
1.0%
130 15
 
0.9%
158 15
 
0.9%
166 15
 
0.9%
150 15
 
0.9%
128 15
 
0.9%
129 15
 
0.9%
Other values (398) 1479
90.2%
ValueCountFrequency (%)
2 1
 
0.1%
3 1
 
0.1%
5 2
0.1%
7 1
 
0.1%
8 3
0.2%
9 4
0.2%
10 3
0.2%
11 1
 
0.1%
12 3
0.2%
13 3
0.2%
ValueCountFrequency (%)
616 1
0.1%
615 1
0.1%
602 1
0.1%
590 1
0.1%
585 1
0.1%
582 1
0.1%
568 1
0.1%
555 1
0.1%
548 1
0.1%
546 2
0.1%

Interactions

2023-12-12T16:04:22.499045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:18.674820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.307605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.084185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.745737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.810431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.617918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:18.777487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.447847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.184526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.854669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.923831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.749877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:18.872078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.591526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.305471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.958709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.026169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.860219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:18.977588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.731489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.409038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.433961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.127272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.977661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.078018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.827861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.520973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.549690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.240355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:23.089145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.187702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:19.950066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:20.634301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:21.695884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:04:22.371650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:04:28.761666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처리과기관코드구기록물생산기관명업로드기관생산년도권호수기록물형태보존기간건수쪽수이미지수량
처리과기관코드1.0001.0000.9240.5100.0000.0000.3780.4830.2780.278
구기록물생산기관명1.0001.0001.0000.8930.0001.0000.9140.7010.5780.578
업로드기관0.9241.0001.0000.7250.1790.0000.3990.4740.2400.240
생산년도0.5100.8930.7251.0000.2530.0850.5880.4630.4290.428
권호수0.0000.0000.1790.2531.0000.0000.2140.0000.0980.097
기록물형태0.0001.0000.0000.0850.0001.0000.0050.0000.1000.100
보존기간0.3780.9140.3990.5880.2140.0051.0000.1870.3990.399
건수0.4830.7010.4740.4630.0000.0000.1871.0000.0880.088
쪽수0.2780.5780.2400.4290.0980.1000.3990.0881.0001.000
이미지수량0.2780.5780.2400.4280.0970.1000.3990.0881.0001.000
2023-12-12T16:04:29.215692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업로드기관보존기간기록물형태
업로드기관1.0000.1460.000
보존기간0.1461.0000.008
기록물형태0.0000.0081.000
2023-12-12T16:04:29.317468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처리과기관코드생산년도권호수건수쪽수이미지수량업로드기관기록물형태보존기간
처리과기관코드1.000-0.184-0.0310.217-0.093-0.0930.6680.0000.140
생산년도-0.1841.000-0.1020.338-0.047-0.0470.5820.0650.428
권호수-0.031-0.1021.000-0.0740.0820.0820.0750.0000.090
건수0.2170.338-0.0741.000-0.129-0.1290.3240.0000.113
쪽수-0.093-0.0470.082-0.1291.0001.0000.1470.0760.261
이미지수량-0.093-0.0470.082-0.1291.0001.0000.1470.0760.261
업로드기관0.6680.5820.0750.3240.1470.1471.0000.0000.146
기록물형태0.0000.0650.0000.0000.0760.0760.0001.0000.008
보존기간0.1400.4280.0900.1130.2610.2610.1460.0081.000

Missing values

2023-12-12T16:04:23.256236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:04:23.442796image/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

관리번호처리과기관코드구기록물생산기관명업로드기관생산년도권호수서비스철제목기록물형태보존기간건수쪽수이미지수량
0GA00162936480000경상남도경상남도19611사령원부일반문서영구18484
1GA00162946480000경상남도경상남도19711농기업화촉진자금일반문서영구6107107
2GA0016295-0016480000경상남도경상남도19761자가용전기공작물허가업체대장(2-1)일반문서준영구1141141
3GA0016295-0026480000경상남도경상남도19762자가용전기공작물허가업체대장(2-2)일반문서준영구1140140
4GA00162966480000경상남도경상남도19761직제.정원일반문서준영구5152152
5GA00162976480000경상남도경상남도1978178절대농지예정조서(김해군)일반문서준영구16464
6GA00162986480000경상남도경상남도1978178절대농지조서(임야)(창녕1-1)일반문서준영구177
7GA0016299-0016480000경상남도경상남도1978178절대농지조서(전)(창녕1-1)(2-1)일반문서준영구1458458
8GA0016299-0026480000경상남도경상남도1978278절대농지조서(전)(창녕1-1)(2-2)일반문서준영구1390390
9GA0016300-0016480000경상남도경상남도19781절대농지예정조서(답)(의령군)(화정/용덕/정곡/지정)(2-1)일반문서준영구1373373
관리번호처리과기관코드구기록물생산기관명업로드기관생산년도권호수서비스철제목기록물형태보존기간건수쪽수이미지수량
1629GA00195059932419경상남도 거제군거제군19501분배농지상환대장(장승포2)일반문서영구17676
1630GA00195069932419경상남도 거제군거제군19501분배농지상환대장(하정)일반문서영구1144144
1631GA00195079932419경상남도 거제군거제군19501분배농지상환대장(하청)일반문서영구1154154
1632GA00195499932455경상남도 거제군 장승포거제군19501분배농지상환대장(장승포1)일반문서영구1161161
1633GA0019550-0019932455경상남도 거제군 장승포거제군19501분배농지상환대장(장승포3)(2-1)일반문서영구1110110
1634GA0019550-0029932455경상남도 거제군 장승포거제군19502분배농지상환대장(장승포3)(2-2)일반문서영구1106106
1635GA00195519932459경상남도 거제군 둔덕거제군19501분배농지상환대장(둔덕4)일반문서영구1200200
1636GB00000426480508경상남도 제승당관리사무소경상남도19771중요문화재 도해도면영구188
1637GB00000436480508경상남도 제승당관리사무소경상남도19771한산도 제승당 시설 보완공사(조경설계도)도면영구11515
1638GB00000446480508경상남도 제승당관리사무소경상남도19771한산도 제승당보수 정화공사(설계도)도면영구17777