Overview

Dataset statistics

Number of variables7
Number of observations66
Missing cells2
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory59.0 B

Variable types

Text4
Numeric1
Boolean1
Categorical1

Dataset

Description부산광역시에서 운영하고있는 통합자금시스템의 보고서관리정보 데이터로 엠알디(MRD)명,에스피(SP)명,등록일시,보고서(ID),보고서명,사용여부,업무구분 정로를 제공합니다.
URLhttps://www.data.go.kr/data/15121613/fileData.do

Alerts

사용여부 has constant value ""Constant
사용여부 has 2 (3.0%) missing valuesMissing
등록일시 has unique valuesUnique
보고서(ID) has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:34:03.415298
Analysis finished2023-12-12 18:34:04.255188
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

엠알디(MRD)명
Text

Distinct59
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-13T03:34:04.491821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.969697
Min length13

Characters and Unicode

Total characters922
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)78.8%

Sample

1st rowTI_RP_3020.mrd
2nd rowCM_RP_1310.mrd
3rd rowCM_RP_3010.mrd
4th rowCM_RP_3020.mrd
5th rowCM_RP_3030.mrd
ValueCountFrequency (%)
ti_rp_3002.mrd 2
 
3.0%
to_rp_2002.mrd 2
 
3.0%
to_rp_2003.mrd 2
 
3.0%
to_rp_2012.mrd 2
 
3.0%
ti_rp_3004.mrd 2
 
3.0%
samplemrd.mrd 2
 
3.0%
ti_rp_3001.mrd 2
 
3.0%
ti_rp_3008.mrd 1
 
1.5%
to_rp_2034.mrd 1
 
1.5%
ti_rp_2099.mrd 1
 
1.5%
Other values (49) 49
74.2%
2023-12-13T03:34:05.047518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 128
13.9%
0 101
11.0%
m 70
 
7.6%
r 68
 
7.4%
d 68
 
7.4%
. 66
 
7.2%
R 64
 
6.9%
P 64
 
6.9%
2 51
 
5.5%
T 50
 
5.4%
Other values (17) 192
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 256
27.8%
Uppercase Letter 256
27.8%
Lowercase Letter 216
23.4%
Connector Punctuation 128
13.9%
Other Punctuation 66
 
7.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
39.5%
2 51
19.9%
3 35
 
13.7%
1 35
 
13.7%
4 9
 
3.5%
6 6
 
2.3%
9 6
 
2.3%
5 5
 
2.0%
8 4
 
1.6%
7 4
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
m 70
32.4%
r 68
31.5%
d 68
31.5%
s 2
 
0.9%
a 2
 
0.9%
p 2
 
0.9%
l 2
 
0.9%
e 2
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
R 64
25.0%
P 64
25.0%
T 50
19.5%
I 28
10.9%
O 22
 
8.6%
C 14
 
5.5%
M 14
 
5.5%
Connector Punctuation
ValueCountFrequency (%)
_ 128
100.0%
Other Punctuation
ValueCountFrequency (%)
. 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 472
51.2%
Common 450
48.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 70
14.8%
r 68
14.4%
d 68
14.4%
R 64
13.6%
P 64
13.6%
T 50
10.6%
I 28
 
5.9%
O 22
 
4.7%
C 14
 
3.0%
M 14
 
3.0%
Other values (5) 10
 
2.1%
Common
ValueCountFrequency (%)
_ 128
28.4%
0 101
22.4%
. 66
14.7%
2 51
 
11.3%
3 35
 
7.8%
1 35
 
7.8%
4 9
 
2.0%
6 6
 
1.3%
9 6
 
1.3%
5 5
 
1.1%
Other values (2) 8
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 128
13.9%
0 101
11.0%
m 70
 
7.6%
r 68
 
7.4%
d 68
 
7.4%
. 66
 
7.2%
R 64
 
6.9%
P 64
 
6.9%
2 51
 
5.5%
T 50
 
5.4%
Other values (17) 192
20.8%

에스피(SP)명
Text

Distinct60
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-13T03:34:05.395588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.954545
Min length11

Characters and Unicode

Total characters855
Distinct characters20
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

Unique54 ?
Unique (%)81.8%

Sample

1st rowSP_TI_RP_3020
2nd rowSP_CM_RP_1310
3rd rowSP_CM_RP_3010
4th rowSP_CM_RP_3020
5th rowSP_CM_RP_3030
ValueCountFrequency (%)
sp_ti_rp_3002 2
 
3.0%
sp_to_rp_2003 2
 
3.0%
sp_to_rp_2012 2
 
3.0%
sp_ti_rp_3001 2
 
3.0%
sp_ti_rp_3004 2
 
3.0%
sp_to_rp_2002 2
 
3.0%
sp_ti_rp_3015 1
 
1.5%
sp_to_rp_2005 1
 
1.5%
sp_to_rp_2004 1
 
1.5%
sp_ti_rp_2099 1
 
1.5%
Other values (50) 50
75.8%
2023-12-13T03:34:05.940724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 195
22.8%
P 130
15.2%
0 107
12.5%
S 68
 
8.0%
R 64
 
7.5%
T 54
 
6.3%
2 51
 
6.0%
1 37
 
4.3%
3 35
 
4.1%
I 28
 
3.3%
Other values (10) 86
10.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 396
46.3%
Decimal Number 264
30.9%
Connector Punctuation 195
22.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 107
40.5%
2 51
19.3%
1 37
 
14.0%
3 35
 
13.3%
4 9
 
3.4%
9 6
 
2.3%
6 6
 
2.3%
5 5
 
1.9%
8 4
 
1.5%
7 4
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
P 130
32.8%
S 68
17.2%
R 64
16.2%
T 54
13.6%
I 28
 
7.1%
O 22
 
5.6%
C 14
 
3.5%
M 14
 
3.5%
E 2
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_ 195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 459
53.7%
Latin 396
46.3%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 195
42.5%
0 107
23.3%
2 51
 
11.1%
1 37
 
8.1%
3 35
 
7.6%
4 9
 
2.0%
9 6
 
1.3%
6 6
 
1.3%
5 5
 
1.1%
8 4
 
0.9%
Latin
ValueCountFrequency (%)
P 130
32.8%
S 68
17.2%
R 64
16.2%
T 54
13.6%
I 28
 
7.1%
O 22
 
5.6%
C 14
 
3.5%
M 14
 
3.5%
E 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 195
22.8%
P 130
15.2%
0 107
12.5%
S 68
 
8.0%
R 64
 
7.5%
T 54
 
6.3%
2 51
 
6.0%
1 37
 
4.3%
3 35
 
4.1%
I 28
 
3.3%
Other values (10) 86
10.1%

등록일시
Real number (ℝ)

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0125093 × 1013
Minimum2.0120727 × 1013
Maximum2.0150507 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2023-12-13T03:34:06.119840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0120727 × 1013
5-th percentile2.0120816 × 1013
Q12.0120915 × 1013
median2.0121221 × 1013
Q32.0130108 × 1013
95-th percentile2.0130586 × 1013
Maximum2.0150507 × 1013
Range2.9780133 × 1010
Interquartile range (IQR)9.1931607 × 109

Descriptive statistics

Standard deviation5.5345723 × 109
Coefficient of variation (CV)0.00027500853
Kurtosis4.8919373
Mean2.0125093 × 1013
Median Absolute Deviation (MAD)4.0261467 × 108
Skewness1.6215075
Sum1.3282562 × 1015
Variance3.063149 × 1019
MonotonicityNot monotonic
2023-12-13T03:34:06.338387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121224133308 1
 
1.5%
20120814034136 1
 
1.5%
20130102184517 1
 
1.5%
20120820012233 1
 
1.5%
20130102183511 1
 
1.5%
20150507174905 1
 
1.5%
20130108200510 1
 
1.5%
20130108195720 1
 
1.5%
20130108195026 1
 
1.5%
20130108201034 1
 
1.5%
Other values (56) 56
84.8%
ValueCountFrequency (%)
20120727042014 1
1.5%
20120801030713 1
1.5%
20120814034136 1
1.5%
20120816021616 1
1.5%
20120816115226 1
1.5%
20120817020401 1
1.5%
20120820012233 1
1.5%
20120820013544 1
1.5%
20120820021622 1
1.5%
20120820022805 1
1.5%
ValueCountFrequency (%)
20150507174905 1
1.5%
20131120164042 1
1.5%
20131120163346 1
1.5%
20130612181923 1
1.5%
20130509174956 1
1.5%
20130423172306 1
1.5%
20130328185211 1
1.5%
20130218195701 1
1.5%
20130116193710 1
1.5%
20130116193325 1
1.5%

보고서(ID)
Text

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-13T03:34:06.694633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters396
Distinct characters15
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

Unique66 ?
Unique (%)100.0%

Sample

1st rowti3020
2nd rowcm1310
3rd rowcm3010
4th rowcm3020
5th rowcm3030
ValueCountFrequency (%)
ti3020 1
 
1.5%
to2010 1
 
1.5%
cm1311 1
 
1.5%
ti3007 1
 
1.5%
ti3008 1
 
1.5%
ti3012 1
 
1.5%
ti3013 1
 
1.5%
ti3015 1
 
1.5%
to2002 1
 
1.5%
to2003 1
 
1.5%
Other values (56) 56
84.8%
2023-12-13T03:34:07.245563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 106
26.8%
t 50
12.6%
2 50
12.6%
3 36
 
9.1%
1 36
 
9.1%
i 28
 
7.1%
o 24
 
6.1%
c 16
 
4.0%
m 14
 
3.5%
4 8
 
2.0%
Other values (5) 28
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 264
66.7%
Lowercase Letter 132
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
40.2%
2 50
18.9%
3 36
 
13.6%
1 36
 
13.6%
4 8
 
3.0%
5 6
 
2.3%
6 6
 
2.3%
9 6
 
2.3%
7 5
 
1.9%
8 5
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
t 50
37.9%
i 28
21.2%
o 24
18.2%
c 16
 
12.1%
m 14
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
Common 264
66.7%
Latin 132
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 106
40.2%
2 50
18.9%
3 36
 
13.6%
1 36
 
13.6%
4 8
 
3.0%
5 6
 
2.3%
6 6
 
2.3%
9 6
 
2.3%
7 5
 
1.9%
8 5
 
1.9%
Latin
ValueCountFrequency (%)
t 50
37.9%
i 28
21.2%
o 24
18.2%
c 16
 
12.1%
m 14
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106
26.8%
t 50
12.6%
2 50
12.6%
3 36
 
9.1%
1 36
 
9.1%
i 28
 
7.1%
o 24
 
6.1%
c 16
 
4.0%
m 14
 
3.5%
4 8
 
2.0%
Other values (5) 28
 
7.1%

보고서명
Text

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size660.0 B
2023-12-13T03:34:07.546107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.2727273
Min length4

Characters and Unicode

Total characters480
Distinct characters81
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)65.2%

Sample

1st row세입월계표(회계별)
2nd row기금일계표조회
3rd row이자 발생 명세표
4th row잔액 확인서
5th row회계별자금운용현황표
ValueCountFrequency (%)
세출일계표 4
 
5.6%
세입세출일계표 3
 
4.2%
월별추세 2
 
2.8%
연도별추세 2
 
2.8%
분기별추세 2
 
2.8%
수납일계표 2
 
2.8%
세입월계표 2
 
2.8%
세입금내역장 2
 
2.8%
세출월계표 2
 
2.8%
테스트보고서 2
 
2.8%
Other values (47) 48
67.6%
2023-12-13T03:34:08.029554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 45
 
9.4%
계 43
 
9.0%
표 41
 
8.5%
일 33
 
6.9%
별 19
 
4.0%
금 18
 
3.8%
출 17
 
3.5%
입 16
 
3.3%
자 13
 
2.7%
집 12
 
2.5%
Other values (71) 223
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 465
96.9%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%
Space Separator 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 45
 
9.7%
계 43
 
9.2%
표 41
 
8.8%
일 33
 
7.1%
별 19
 
4.1%
금 18
 
3.9%
출 17
 
3.7%
입 16
 
3.4%
자 13
 
2.8%
집 12
 
2.6%
Other values (68) 208
44.7%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 465
96.9%
Common 15
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 45
 
9.7%
계 43
 
9.2%
표 41
 
8.8%
일 33
 
7.1%
별 19
 
4.1%
금 18
 
3.9%
출 17
 
3.7%
입 16
 
3.4%
자 13
 
2.8%
집 12
 
2.6%
Other values (68) 208
44.7%
Common
ValueCountFrequency (%)
( 5
33.3%
) 5
33.3%
5
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 465
96.9%
ASCII 15
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 45
 
9.7%
계 43
 
9.2%
표 41
 
8.8%
일 33
 
7.1%
별 19
 
4.1%
금 18
 
3.9%
출 17
 
3.7%
입 16
 
3.4%
자 13
 
2.8%
집 12
 
2.6%
Other values (68) 208
44.7%
ASCII
ValueCountFrequency (%)
( 5
33.3%
) 5
33.3%
5
33.3%

사용여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.6%
Missing2
Missing (%)3.0%
Memory size264.0 B
True
64 
(Missing)
 
2
ValueCountFrequency (%)
True 64
97.0%
(Missing) 2
 
3.0%
2023-12-13T03:34:08.164067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

업무구분
Categorical

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
TI
28 
TO
22 
CM
14 
CO
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTI
2nd rowCM
3rd rowCM
4th rowCM
5th rowCM

Common Values

ValueCountFrequency (%)
TI 28
42.4%
TO 22
33.3%
CM 14
21.2%
CO 2
 
3.0%

Length

2023-12-13T03:34:08.279013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:34:08.382279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ti 28
42.4%
to 22
33.3%
cm 14
21.2%
co 2
 
3.0%

Interactions

2023-12-13T03:34:03.831327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:34:08.478423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
엠알디(MRD)명에스피(SP)명등록일시보고서(ID)보고서명업무구분
엠알디(MRD)명1.0001.0001.0001.0001.0001.000
에스피(SP)명1.0001.0001.0001.0001.0001.000
등록일시1.0001.0001.0001.0000.9710.241
보고서(ID)1.0001.0001.0001.0001.0001.000
보고서명1.0001.0000.9711.0001.0000.982
업무구분1.0001.0000.2411.0000.9821.000
2023-12-13T03:34:08.586526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일시업무구분
등록일시1.0000.238
업무구분0.2381.000

Missing values

2023-12-13T03:34:04.025173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:34:04.201374image/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

엠알디(MRD)명에스피(SP)명등록일시보고서(ID)보고서명사용여부업무구분
0TI_RP_3020.mrdSP_TI_RP_302020121224133308ti3020세입월계표(회계별)<NA>TI
1CM_RP_1310.mrdSP_CM_RP_131020120925022600cm1310기금일계표조회YCM
2CM_RP_3010.mrdSP_CM_RP_301020131120163346cm3010이자 발생 명세표YCM
3CM_RP_3020.mrdSP_CM_RP_302020120911120326cm3020잔액 확인서YCM
4CM_RP_3030.mrdSP_CM_RP_303020120921031249cm3030회계별자금운용현황표YCM
5CM_RP_3040.mrdSP_CM_RP_304020120921032635cm3040계좌별자금운용현황표YCM
6CM_RP_3050.mrdSP_CM_RP_305020120913043256cm3050부산시청예금일계표YCM
7CM_RP_3060.mrdSP_CM_RP_306020120924030409cm3060일자별계좌별잔액조회YCM
8CM_RP_3070.mrdSP_CM_RP_307020121019170543cm3070일상경비잔액확인서YCM
9CM_RP_3080.mrdSP_CM_RP_308020131120164042cm3080이자발생명세표(구청)YCM
엠알디(MRD)명에스피(SP)명등록일시보고서(ID)보고서명사용여부업무구분
56TO_RP_2019.mrdSP_TO_RP_201920130108201438to2019월별추세YTO
57TO_RP_2020.mrdSP_TO_RP_202020130108201706to2020분기별추세YTO
58TO_RP_2021.mrdSP_TO_RP_202120130108201936to2021연도별추세YTO
59TO_RP_2023.mrdSP_TO_RP_202320130116193325to2023일상경비세입월계표YTO
60TO_RP_2024.mrdSP_TO_RP_202420130116193710to2024세출금내역장YTO
61TI_RP_3018.mrdSP_TI_RP_301820130218195701ti3018보고서(부서용)YTI
62TO_RP_2034.mrdSP_TO_RP_203420121218110331to2034세입세출외현금일계표YTO
63TI_RP_2099.mrdSP_TI_RP_209920130423172306ti2099일반회계세입일보 대사<NA>TI
64CM_RP_1311.mrdSP_CM_RP_131120121205102218cm1311기금총괄표(기금종류별)YCM
65CM_RP_1312.mrdSP_CM_RP_131220121205102431cm1312기금총괄표(예금종류별)YCM