Overview

Dataset statistics

Number of variables4
Number of observations275
Missing cells243
Missing cells (%)22.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.3 KiB
Average record size in memory34.5 B

Variable types

Categorical1
Text2
Numeric1

Dataset

Description복식부기 재무현황(비용)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ATRXJMQN2U60Q3Q8842G22457038&infSeq=1

Alerts

시군명 has 243 (88.4%) missing valuesMissing
비용총계액(원) has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:13:06.057547
Analysis finished2023-12-10 21:13:06.769883
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2020
243 
2021
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

Length

2023-12-11T06:13:06.838596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:13:06.961265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 243
88.4%
2021 32
 
11.6%

시군명
Text

MISSING 

Distinct32
Distinct (%)100.0%
Missing243
Missing (%)88.4%
Memory size2.3 KiB
2023-12-11T06:13:07.154225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.09375
Min length3

Characters and Unicode

Total characters99
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row가평군
2nd row경기도
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
경기도 1
 
3.1%
고양시 1
 
3.1%
화성시 1
 
3.1%
하남시 1
 
3.1%
포천시 1
 
3.1%
평택시 1
 
3.1%
파주시 1
 
3.1%
이천시 1
 
3.1%
의정부시 1
 
3.1%
의왕시 1
 
3.1%
Other values (22) 22
68.8%
2023-12-11T06:13:07.538813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.3%
천 6
 
6.1%
주 5
 
5.1%
양 5
 
5.1%
군 4
 
4.0%
안 3
 
3.0%
평 3
 
3.0%
남 3
 
3.0%
포 3
 
3.0%
성 3
 
3.0%
Other values (31) 35
35.4%

자치단체명
Text

Distinct243
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T06:13:07.870194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8872727
Min length4

Characters and Unicode

Total characters1344
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)76.7%

Sample

1st row경기가평군
2nd row경기본청
3rd row경기고양시
4th row경기과천시
5th row경기광명시
ValueCountFrequency (%)
경기가평군 2
 
0.7%
경기평택시 2
 
0.7%
경기안성시 2
 
0.7%
경기여주시 2
 
0.7%
경기용인시 2
 
0.7%
경기연천군 2
 
0.7%
경기양평군 2
 
0.7%
경기의왕시 2
 
0.7%
경기하남시 2
 
0.7%
경기이천시 2
 
0.7%
Other values (233) 255
92.7%
2023-12-11T06:13:08.373970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 110
 
8.2%
시 105
 
7.8%
군 89
 
6.6%
구 84
 
6.2%
남 73
 
5.4%
기 65
 
4.8%
북 57
 
4.2%
전 45
 
3.3%
산 41
 
3.1%
천 39
 
2.9%
Other values (123) 636
47.3%

비용총계액(원)
Real number (ℝ)

UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6028868 × 1012
Minimum1.5950236 × 1011
Maximum3.971671 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:13:08.561140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5950236 × 1011
5-th percentile3.3451732 × 1011
Q14.6529345 × 1011
median7.1522833 × 1011
Q31.145204 × 1012
95-th percentile5.5676719 × 1012
Maximum3.971671 × 1013
Range3.9557208 × 1013
Interquartile range (IQR)6.7991053 × 1011

Descriptive statistics

Standard deviation4.00623 × 1012
Coefficient of variation (CV)2.4993842
Kurtosis58.540763
Mean1.6028868 × 1012
Median Absolute Deviation (MAD)2.8208082 × 1011
Skewness7.2016667
Sum4.4079388 × 1014
Variance1.6049879 × 1025
MonotonicityNot monotonic
2023-12-11T06:13:08.734183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
493265505379 1
 
0.4%
614578084003 1
 
0.4%
437081038951 1
 
0.4%
686539419683 1
 
0.4%
773143882324 1
 
0.4%
493888596560 1
 
0.4%
834343156907 1
 
0.4%
924523928944 1
 
0.4%
707265487713 1
 
0.4%
1320363884118 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
159502356626 1
0.4%
179033108150 1
0.4%
206298609165 1
0.4%
211656013193 1
0.4%
235830161126 1
0.4%
256232941539 1
0.4%
284228054265 1
0.4%
285910690972 1
0.4%
289465924105 1
0.4%
302417288420 1
0.4%
ValueCountFrequency (%)
39716710414043 1
0.4%
34744674854922 1
0.4%
32286360865796 1
0.4%
12733415610591 1
0.4%
10934590254347 1
0.4%
10865218627760 1
0.4%
10604692743844 1
0.4%
9271130728050 1
0.4%
9049549002377 1
0.4%
8067805256487 1
0.4%

Interactions

2023-12-11T06:13:06.489125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:13:08.825920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명비용총계액(원)
회계연도1.000NaN0.000
시군명NaN1.0001.000
비용총계액(원)0.0001.0001.000
2023-12-11T06:13:08.940004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용총계액(원)회계연도
비용총계액(원)1.0000.000
회계연도0.0001.000

Missing values

2023-12-11T06:13:06.634461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:13:06.734364image/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

회계연도시군명자치단체명비용총계액(원)
02021가평군경기가평군493265505379
12021경기도경기본청34744674854922
22021고양시경기고양시2756061280836
32021과천시경기과천시404631720084
42021광명시경기광명시867935676235
52021광주시경기광주시1232409855899
62021구리시경기구리시604744000089
72021군포시경기군포시761311430396
82021김포시경기김포시1419546988787
92021남양주시경기남양주시1945885539164
회계연도시군명자치단체명비용총계액(원)
2652020<NA>전남화순군585697725508
2662020<NA>전남장흥군466112982394
2672020<NA>전남강진군421802312826
2682020<NA>전남해남군733261896413
2692020<NA>전남영암군564856672562
2702020<NA>전남무안군552494490857
2712020<NA>전남영광군508860016403
2722020<NA>전남장성군384617737056
2732020<NA>전남완도군533690977424
2742020<NA>전남진도군409310918871