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(자산)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=D5JMCG1JS84LBJN2TXHA22478524&infSeq=1

Alerts

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

Reproduction

Analysis started2023-12-10 21:53:25.353449
Analysis finished2023-12-10 21:53:25.717018
Duration0.36 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

2023-12-11T06:53:25.814813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:53:25.914810image/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
2023-12-11T06:53:26.070439image/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%
2023-12-11T06:53:26.357884image/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
2023-12-11T06:53:26.625446image/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%
2023-12-11T06:53:27.017271image/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%

자산총계액(원)
Real number (ℝ)

UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9096475 × 1012
Minimum3.7768489 × 1011
Maximum1.4125753 × 1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:53:27.166618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.7768489 × 1011
5-th percentile8.8287669 × 1011
Q11.9803204 × 1012
median2.9262712 × 1012
Q35.4005826 × 1012
95-th percentile2.0249406 × 1013
Maximum1.4125753 × 1014
Range1.4087985 × 1014
Interquartile range (IQR)3.4202622 × 1012

Descriptive statistics

Standard deviation1.1018157 × 1013
Coefficient of variation (CV)1.8644355
Kurtosis85.823406
Mean5.9096475 × 1012
Median Absolute Deviation (MAD)1.2172487 × 1012
Skewness7.8649537
Sum1.625153 × 1015
Variance1.2139977 × 1026
MonotonicityNot monotonic
2023-12-11T06:53:27.325198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2366944425649 1
 
0.4%
6988726567332 1
 
0.4%
4651646758114 1
 
0.4%
4213692483554 1
 
0.4%
3655207097456 1
 
0.4%
7360385620574 1
 
0.4%
5578957429955 1
 
0.4%
4381369828532 1
 
0.4%
9081068643880 1
 
0.4%
3010673925752 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
377684892354 1
0.4%
524410176802 1
0.4%
563340703829 1
0.4%
600887299025 1
0.4%
628718155930 1
0.4%
652135343732 1
0.4%
681027401103 1
0.4%
700404028005 1
0.4%
737520967115 1
0.4%
780314710263 1
0.4%
ValueCountFrequency (%)
141257533321371 1
0.4%
58927573376048 1
0.4%
46801850561560 1
0.4%
41057060680369 1
0.4%
39753749837739 1
0.4%
35621211513039 1
0.4%
28052651761418 1
0.4%
25407634783325 1
0.4%
24286520435638 1
0.4%
23821892369558 1
0.4%

Interactions

2023-12-11T06:53:25.505319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:53:27.440346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명자산총계액(원)
회계연도1.000NaN0.023
시군명NaN1.0001.000
자산총계액(원)0.0231.0001.000
2023-12-11T06:53:27.540503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자산총계액(원)회계연도
자산총계액(원)1.0000.019
회계연도0.0191.000

Missing values

2023-12-11T06:53:25.612610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:53:25.687064image/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

회계연도시군명자치단체명자산총계액(원)
02021가평군경기가평군2366944425649
12021경기도경기본청41057060680369
22021고양시경기고양시20012512146484
32021과천시경기과천시2304366556782
42021광명시경기광명시3883276891158
52021광주시경기광주시4125270688712
62021구리시경기구리시3668249514239
72021군포시경기군포시4457035860217
82021김포시경기김포시7651733765856
92021남양주시경기남양주시8272961068298
회계연도시군명자치단체명자산총계액(원)
2652020<NA>부산사상구993903704125
2662020<NA>대구본청35621211513039
2672020<NA>대구중구700404028005
2682020<NA>대구동구1600283514300
2692020<NA>대구서구979758780980
2702020<NA>대구남구524410176802
2712020<NA>대구북구1297881490672
2722020<NA>대구달서구1488238027204
2732020<NA>대구달성군3475117427258
2742020<NA>인천본청58927573376048