Overview

Dataset statistics

Number of variables13
Number of observations328
Missing cells36
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.0 KiB
Average record size in memory109.4 B

Variable types

Numeric5
Categorical5
DateTime2
Text1

Dataset

Description광주교통공사 간행물 발간정보에 대한 데이터로 구분, 기관번호, 기능분휴, 형식구분, 연도, 등록일자 자료명 등 정보를 제공합니다.
Author광주교통공사
URLhttps://www.data.go.kr/data/3046434/fileData.do

Alerts

연번 is highly overall correlated with 연도High correlation
기능분류 is highly overall correlated with 형식구분High correlation
연도 is highly overall correlated with 연번High correlation
발행부수 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 발행부수 and 3 other fieldsHigh correlation
기관번호 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
형식구분 is highly overall correlated with 기능분류 and 3 other fieldsHigh correlation
편집부서 is highly overall correlated with 구분 and 3 other fieldsHigh correlation
크기 is highly overall correlated with 기관번호 and 1 other fieldsHigh correlation
크기 is highly imbalanced (90.1%)Imbalance
발행부수 has 12 (3.7%) missing valuesMissing
페이지 has 24 (7.3%) missing valuesMissing
연번 has unique valuesUnique
기능분류 has 11 (3.4%) zerosZeros

Reproduction

Analysis started2024-04-29 23:21:31.274478
Analysis finished2024-04-29 23:21:36.168251
Duration4.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct328
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164.5
Minimum1
Maximum328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-30T08:21:36.233119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.35
Q182.75
median164.5
Q3246.25
95-th percentile311.65
Maximum328
Range327
Interquartile range (IQR)163.5

Descriptive statistics

Standard deviation94.829672
Coefficient of variation (CV)0.57647217
Kurtosis-1.2
Mean164.5
Median Absolute Deviation (MAD)82
Skewness0
Sum53956
Variance8992.6667
MonotonicityStrictly increasing
2024-04-30T08:21:36.356016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
227 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
Other values (318) 318
97.0%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
정기
183 
부정기
145 

Length

Max length3
Median length2
Mean length2.4420732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정기
2nd row부정기
3rd row정기
4th row정기
5th row정기

Common Values

ValueCountFrequency (%)
정기 183
55.8%
부정기 145
44.2%

Length

2024-04-30T08:21:36.483291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:21:36.572840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기 183
55.8%
부정기 145
44.2%

기관번호
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
인재
44 
재정
41 
성과
35 
차량
26 
경영
25 
Other values (25)
157 

Length

Max length5
Median length2
Mean length2.0792683
Min length2

Unique

Unique9 ?
Unique (%)2.7%

Sample

1st row자산
2nd row홍보
3rd row자산
4th row재정
5th row경영

Common Values

ValueCountFrequency (%)
인재 44
13.4%
재정 41
12.5%
성과 35
10.7%
차량 26
7.9%
경영 25
7.6%
전략 23
 
7.0%
안전 21
 
6.4%
자산 20
 
6.1%
기획 19
 
5.8%
홍보 14
 
4.3%
Other values (20) 60
18.3%

Length

2024-04-30T08:21:36.681588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인재 44
13.4%
재정 41
12.5%
성과 35
10.7%
차량 26
7.9%
경영 25
7.6%
전략 23
 
7.0%
안전 21
 
6.4%
자산 20
 
6.1%
기획 19
 
5.8%
홍보 14
 
4.3%
Other values (20) 60
18.3%

기능분류
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean372.79268
Minimum0
Maximum30403
Zeros11
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-30T08:21:36.789479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1101
median204
Q3404
95-th percentile800
Maximum30403
Range30403
Interquartile range (IQR)303

Descriptive statistics

Standard deviation1677.1952
Coefficient of variation (CV)4.4990025
Kurtosis317.09837
Mean372.79268
Median Absolute Deviation (MAD)104
Skewness17.66128
Sum122276
Variance2812983.8
MonotonicityNot monotonic
2024-04-30T08:21:36.900502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
100 66
20.1%
404 43
13.1%
204 26
 
7.9%
301 19
 
5.8%
101 19
 
5.8%
104 14
 
4.3%
0 11
 
3.4%
103 11
 
3.4%
302 11
 
3.4%
500 10
 
3.0%
Other values (25) 98
29.9%
ValueCountFrequency (%)
0 11
 
3.4%
1 3
 
0.9%
100 66
20.1%
101 19
 
5.8%
102 7
 
2.1%
103 11
 
3.4%
104 14
 
4.3%
200 5
 
1.5%
202 3
 
0.9%
203 7
 
2.1%
ValueCountFrequency (%)
30403 1
 
0.3%
903 1
 
0.3%
902 4
1.2%
901 2
 
0.6%
900 6
1.8%
802 1
 
0.3%
801 1
 
0.3%
800 2
 
0.6%
701 1
 
0.3%
700 5
1.5%

형식구분
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
06_06
103 
06_07
88 
05_06
57 
05_07
23 
07_08
12 
Other values (19)
45 

Length

Max length5
Median length5
Mean length4.9878049
Min length1

Unique

Unique11 ?
Unique (%)3.4%

Sample

1st row06_06
2nd row05_06
3rd row06_06
4th row05_06
5th row05_07

Common Values

ValueCountFrequency (%)
06_06 103
31.4%
06_07 88
26.8%
05_06 57
17.4%
05_07 23
 
7.0%
07_08 12
 
3.7%
07_09 11
 
3.4%
02_06 7
 
2.1%
07_10 4
 
1.2%
07_12 3
 
0.9%
07_11 3
 
0.9%
Other values (14) 17
 
5.2%

Length

2024-04-30T08:21:37.286995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06_06 103
31.4%
06_07 88
26.8%
05_06 57
17.4%
05_07 23
 
7.0%
07_08 12
 
3.7%
07_09 11
 
3.4%
02_06 7
 
2.1%
07_10 4
 
1.2%
07_12 3
 
0.9%
07_11 3
 
0.9%
Other values (14) 17
 
5.2%

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.564
Minimum2003
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-30T08:21:37.397809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2007
Q12010
median2014
Q32020
95-th percentile2023
Maximum2024
Range21
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.5517183
Coefficient of variation (CV)0.0027557915
Kurtosis-1.2794346
Mean2014.564
Median Absolute Deviation (MAD)5
Skewness0.014750677
Sum660777
Variance30.821576
MonotonicityIncreasing
2024-04-30T08:21:37.519675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2008 29
 
8.8%
2009 29
 
8.8%
2022 23
 
7.0%
2023 22
 
6.7%
2018 21
 
6.4%
2021 21
 
6.4%
2020 21
 
6.4%
2010 21
 
6.4%
2011 20
 
6.1%
2012 19
 
5.8%
Other values (12) 102
31.1%
ValueCountFrequency (%)
2003 2
 
0.6%
2004 4
 
1.2%
2005 5
 
1.5%
2006 5
 
1.5%
2007 7
 
2.1%
2008 29
8.8%
2009 29
8.8%
2010 21
6.4%
2011 20
6.1%
2012 19
5.8%
ValueCountFrequency (%)
2024 2
 
0.6%
2023 22
6.7%
2022 23
7.0%
2021 21
6.4%
2020 21
6.4%
2019 15
4.6%
2018 21
6.4%
2017 10
3.0%
2016 11
3.4%
2015 12
3.7%

등록일자
Date

Distinct137
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2003-12-01 00:00:00
Maximum2024-03-27 00:00:00
2024-04-30T08:21:37.635026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:37.772617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

자 료 명
Text

Distinct307
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-04-30T08:21:38.023731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length15.478659
Min length5

Characters and Unicode

Total characters5077
Distinct characters262
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)88.7%

Sample

1st row2003년도 결산서
2nd row2003 직무교육 교재
3rd row2004년도 결산서
4th row2004 원가분석보고서
5th row2004 경영실적 보고서
ValueCountFrequency (%)
예산서 25
 
2.6%
결산서 18
 
1.9%
추경예산서 18
 
1.9%
철도종사자 18
 
1.9%
및 18
 
1.9%
자체경영평가 17
 
1.8%
2023년 13
 
1.4%
결과보고서 12
 
1.3%
전동차 12
 
1.3%
보고서 12
 
1.3%
Other values (366) 787
82.8%
2024-04-30T08:21:38.469008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
622
 
12.3%
2 355
 
7.0%
0 332
 
6.5%
년 183
 
3.6%
1 179
 
3.5%
도 172
 
3.4%
서 165
 
3.2%
경 114
 
2.2%
산 83
 
1.6%
영 72
 
1.4%
Other values (252) 2800
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3280
64.6%
Decimal Number 1044
 
20.6%
Space Separator 622
 
12.3%
Open Punctuation 35
 
0.7%
Close Punctuation 35
 
0.7%
Uppercase Letter 26
 
0.5%
Other Punctuation 15
 
0.3%
Lowercase Letter 7
 
0.1%
Connector Punctuation 5
 
0.1%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
년 183
 
5.6%
도 172
 
5.2%
서 165
 
5.0%
경 114
 
3.5%
산 83
 
2.5%
영 72
 
2.2%
보 72
 
2.2%
사 68
 
2.1%
교 66
 
2.0%
자 66
 
2.0%
Other values (214) 2219
67.7%
Uppercase Letter
ValueCountFrequency (%)
O 5
19.2%
A 3
11.5%
S 3
11.5%
C 3
11.5%
P 2
 
7.7%
V 1
 
3.8%
B 1
 
3.8%
M 1
 
3.8%
D 1
 
3.8%
T 1
 
3.8%
Other values (5) 5
19.2%
Decimal Number
ValueCountFrequency (%)
2 355
34.0%
0 332
31.8%
1 179
17.1%
3 46
 
4.4%
9 32
 
3.1%
8 26
 
2.5%
7 22
 
2.1%
4 20
 
1.9%
6 16
 
1.5%
5 16
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
e 2
28.6%
c 1
 
14.3%
k 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
· 1
 
6.7%
& 1
 
6.7%
Space Separator
ValueCountFrequency (%)
622
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3280
64.6%
Common 1764
34.7%
Latin 33
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
년 183
 
5.6%
도 172
 
5.2%
서 165
 
5.0%
경 114
 
3.5%
산 83
 
2.5%
영 72
 
2.2%
보 72
 
2.2%
사 68
 
2.1%
교 66
 
2.0%
자 66
 
2.0%
Other values (214) 2219
67.7%
Common
ValueCountFrequency (%)
622
35.3%
2 355
20.1%
0 332
18.8%
1 179
 
10.1%
3 46
 
2.6%
( 35
 
2.0%
) 35
 
2.0%
9 32
 
1.8%
8 26
 
1.5%
7 22
 
1.2%
Other values (9) 80
 
4.5%
Latin
ValueCountFrequency (%)
O 5
15.2%
o 3
 
9.1%
A 3
 
9.1%
S 3
 
9.1%
C 3
 
9.1%
e 2
 
6.1%
P 2
 
6.1%
V 1
 
3.0%
c 1
 
3.0%
k 1
 
3.0%
Other values (9) 9
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3280
64.6%
ASCII 1796
35.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
622
34.6%
2 355
19.8%
0 332
18.5%
1 179
 
10.0%
3 46
 
2.6%
( 35
 
1.9%
) 35
 
1.9%
9 32
 
1.8%
8 26
 
1.4%
7 22
 
1.2%
Other values (27) 112
 
6.2%
Hangul
ValueCountFrequency (%)
년 183
 
5.6%
도 172
 
5.2%
서 165
 
5.0%
경 114
 
3.5%
산 83
 
2.5%
영 72
 
2.2%
보 72
 
2.2%
사 68
 
2.1%
교 66
 
2.0%
자 66
 
2.0%
Other values (214) 2219
67.7%
None
ValueCountFrequency (%)
· 1
100.0%

편집부서
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
인재개발
46 
성과
29 
재정운영팀
28 
경영기획팀
23 
전략경영팀
23 
Other values (45)
179 

Length

Max length6
Median length5
Mean length4.0792683
Min length2

Unique

Unique22 ?
Unique (%)6.7%

Sample

1st row자산회계팀
2nd row홍보교육팀
3rd row자산회계팀
4th row재정운영팀
5th row경영기획팀

Common Values

ValueCountFrequency (%)
인재개발 46
14.0%
성과 29
 
8.8%
재정운영팀 28
 
8.5%
경영기획팀 23
 
7.0%
전략경영팀 23
 
7.0%
자산회계팀 17
 
5.2%
안전관리팀 17
 
5.2%
차량 16
 
4.9%
홍보교육팀 13
 
4.0%
기획예산팀 10
 
3.0%
Other values (40) 106
32.3%

Length

2024-04-30T08:21:38.611290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인재개발 46
14.0%
성과 29
 
8.8%
재정운영팀 28
 
8.5%
경영기획팀 23
 
7.0%
전략경영팀 23
 
7.0%
자산회계팀 17
 
5.2%
안전관리팀 17
 
5.2%
차량 16
 
4.9%
홍보교육팀 13
 
4.0%
기획예산팀 10
 
3.0%
Other values (40) 106
32.3%

발행일자
Date

Distinct135
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2003-12-01 00:00:00
Maximum2024-03-27 00:00:00
2024-04-30T08:21:38.724101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:38.853453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발행부수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct44
Distinct (%)13.9%
Missing12
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean57.446203
Minimum6
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-30T08:21:38.983867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile10
Q130
median50
Q370
95-th percentile126.25
Maximum350
Range344
Interquartile range (IQR)40

Descriptive statistics

Standard deviation38.416435
Coefficient of variation (CV)0.66873759
Kurtosis10.809656
Mean57.446203
Median Absolute Deviation (MAD)20
Skewness2.1059505
Sum18153
Variance1475.8225
MonotonicityNot monotonic
2024-04-30T08:21:39.112918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
50 73
22.3%
60 46
14.0%
100 28
 
8.5%
70 23
 
7.0%
10 22
 
6.7%
30 16
 
4.9%
20 9
 
2.7%
25 8
 
2.4%
110 6
 
1.8%
65 6
 
1.8%
Other values (34) 79
24.1%
(Missing) 12
 
3.7%
ValueCountFrequency (%)
6 1
 
0.3%
7 2
 
0.6%
8 2
 
0.6%
9 2
 
0.6%
10 22
6.7%
11 1
 
0.3%
12 3
 
0.9%
13 2
 
0.6%
15 3
 
0.9%
16 4
 
1.2%
ValueCountFrequency (%)
350 1
 
0.3%
200 2
 
0.6%
150 5
 
1.5%
140 5
 
1.5%
130 3
 
0.9%
125 1
 
0.3%
120 4
 
1.2%
110 6
 
1.8%
100 28
8.5%
90 5
 
1.5%

크기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
A4
319 
16절지
 
4
B5
 
3
A5
 
1
11*16
 
1

Length

Max length5
Median length2
Mean length2.0335366
Min length2

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st rowA4
2nd rowA4
3rd rowA4
4th rowA4
5th rowA4

Common Values

ValueCountFrequency (%)
A4 319
97.3%
16절지 4
 
1.2%
B5 3
 
0.9%
A5 1
 
0.3%
11*16 1
 
0.3%

Length

2024-04-30T08:21:39.249398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:21:39.370711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a4 319
97.3%
16절지 4
 
1.2%
b5 3
 
0.9%
a5 1
 
0.3%
11*16 1
 
0.3%

페이지
Real number (ℝ)

MISSING 

Distinct148
Distinct (%)48.7%
Missing24
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean191.17434
Minimum13
Maximum770
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-04-30T08:21:39.493353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile50
Q1100
median138.5
Q3218.5
95-th percentile513.8
Maximum770
Range757
Interquartile range (IQR)118.5

Descriptive statistics

Standard deviation141.81757
Coefficient of variation (CV)0.74182325
Kurtosis3.4595632
Mean191.17434
Median Absolute Deviation (MAD)42.5
Skewness1.8724371
Sum58117
Variance20112.224
MonotonicityNot monotonic
2024-04-30T08:21:39.670976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 34
 
10.4%
130 23
 
7.0%
50 11
 
3.4%
170 7
 
2.1%
200 7
 
2.1%
60 5
 
1.5%
165 4
 
1.2%
120 4
 
1.2%
80 4
 
1.2%
150 4
 
1.2%
Other values (138) 201
61.3%
(Missing) 24
 
7.3%
ValueCountFrequency (%)
13 1
 
0.3%
15 1
 
0.3%
30 1
 
0.3%
35 2
 
0.6%
40 1
 
0.3%
45 1
 
0.3%
46 1
 
0.3%
50 11
3.4%
55 1
 
0.3%
60 5
1.5%
ValueCountFrequency (%)
770 1
0.3%
724 1
0.3%
706 1
0.3%
700 2
0.6%
680 1
0.3%
641 1
0.3%
620 2
0.6%
610 1
0.3%
560 1
0.3%
546 1
0.3%

Interactions

2024-04-30T08:21:35.338110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.512092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.995695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.424679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.835588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.435240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.654005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.077141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.506075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.946668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.524751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.741808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.160017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.580396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.051579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.610344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.822002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.237921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.663264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.159109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.708511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:33.903843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.328840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:34.746470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:21:35.245600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T08:21:39.779793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분기관번호기능분류형식구분연도편집부서발행부수크기페이지
연번1.0000.3840.7930.0000.7070.9730.8290.3600.3630.465
구분0.3841.0000.9610.0000.9860.4460.9530.5470.1260.535
기관번호0.7930.9611.0000.0000.8780.8090.9970.7970.8670.635
기능분류0.0000.0000.0001.0001.0000.0000.5550.0000.0000.000
형식구분0.7070.9860.8781.0001.0000.6970.9440.8090.7020.343
연도0.9730.4460.8090.0000.6971.0000.8320.3520.2220.388
편집부서0.8290.9530.9970.5550.9440.8321.0000.8230.8330.749
발행부수0.3600.5470.7970.0000.8090.3520.8231.0000.0800.375
크기0.3630.1260.8670.0000.7020.2220.8330.0801.0000.353
페이지0.4650.5350.6350.0000.3430.3880.7490.3750.3531.000
2024-04-30T08:21:39.893833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
크기형식구분기관번호편집부서구분
크기1.0000.4170.5550.5210.153
형식구분0.4171.0000.4080.5130.876
기관번호0.5550.4081.0000.8780.820
편집부서0.5210.5130.8781.0000.819
구분0.1530.8760.8200.8191.000
2024-04-30T08:21:39.985917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기능분류연도발행부수페이지구분기관번호형식구분편집부서크기
연번1.0000.4650.998-0.2400.3860.2910.3720.3410.4270.157
기능분류0.4651.0000.468-0.3880.2340.0000.0000.9660.4290.000
연도0.9980.4681.000-0.2330.3890.3300.3940.3330.4350.094
발행부수-0.240-0.388-0.2331.000-0.0860.5830.4700.5000.4690.050
페이지0.3860.2340.389-0.0861.0000.4070.2450.1280.3380.152
구분0.2910.0000.3300.5830.4071.0000.8200.8760.8190.153
기관번호0.3720.0000.3940.4700.2450.8201.0000.4080.8780.555
형식구분0.3410.9660.3330.5000.1280.8760.4081.0000.5130.417
편집부서0.4270.4290.4350.4690.3380.8190.8780.5131.0000.521
크기0.1570.0000.0940.0500.1520.1530.5550.4170.5211.000

Missing values

2024-04-30T08:21:35.831665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:21:36.000017image/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.
2024-04-30T08:21:36.116727image/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

연번구분기관번호기능분류형식구분연도등록일자자 료 명편집부서발행일자발행부수크기페이지
01정기자산30006_0620032003-12-012003년도 결산서자산회계팀2003-12-0150A450
12부정기홍보10105_0620032003-12-012003 직무교육 교재홍보교육팀2003-12-0150A4100
23정기자산30006_0620042004-12-012004년도 결산서자산회계팀2004-12-0150A450
34정기재정10005_0620042004-12-012004 원가분석보고서재정운영팀2004-12-0150A4100
45정기경영10005_0720042004-12-012004 경영실적 보고서경영기획팀2004-12-0150A4130
56정기홍보10105_0620042004-12-012004년 연수결과 보고서홍보교육팀2004-12-0150A4100
67정기자산30006_0620052005-12-012005년도 결산서자산회계팀2005-12-0150A450
78정기재정10005_0620052005-12-012005 원가분석보고서재정운영팀2005-12-0150A4100
89정기전략10005_0620052005-12-012005년 경영실적 보고서전략경영팀2005-12-0150A4100
910정기전략10005_0620052005-12-012005년 경영실적보고서전략경영팀2005-12-0150A4100
연번구분기관번호기능분류형식구분연도등록일자자 료 명편집부서발행일자발행부수크기페이지
318319정기성과20406_0620232023-12-262023년도 제 4회 추가경정 예산서성과2023-12-2665A4125
319320정기성과20406_0620232023-12-262024년도 본예산서성과2023-12-26110A4226
320321부정기인재40406_0720232023-11-012023년 사무직 보수교육 교재인재개발2023-11-0123A4<NA>
321322부정기신호60406_0720232023-11-01정비지침서신호2023-11-018A4377
322323부정기인재40406_0720232023-12-042023년 공무직 신규자교육 교재인재개발2023-12-0412A4240
323324부정기차량60406_0720232023-12-12작업절차서(경정비)차량2023-12-1210A4410
324325부정기차량60406_0720232023-12-12작업절차서(중정비)차량2023-12-1210A4546
325326부정기인재40406_0720232023-12-262023년 신규직원 양성교육 교재인재개발2023-12-2618A4770
326327정기성과20406_0620242024-01-172024년 이체예산서성과2024-01-1765A4236
327328정기자산30403120242024-03-27제22기 2023회계연도 결산서자산회계2024-03-2760A4171