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(수익)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=P6W9UBWDUK6CHKNLZSMY22464694&infSeq=1

Alerts

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

Reproduction

Analysis started2023-12-10 21:59:49.543449
Analysis finished2023-12-10 21:59:49.903235
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

2023-12-11T06:59:49.956385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:59:50.036752image/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
2023-12-11T06:59:50.198744image/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%
2023-12-11T06:59:50.511950image/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
2023-12-11T06:59:50.801450image/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%
2023-12-11T06:59:51.215949image/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%

수익총계액(원)
Real number (ℝ)

UNIQUE 

Distinct275
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6691092 × 1012
Minimum1.9451323 × 1011
Maximum3.7576182 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T06:59:51.352298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9451323 × 1011
5-th percentile3.6931044 × 1011
Q15.2438765 × 1011
median7.9461284 × 1011
Q31.2199283 × 1012
95-th percentile5.624722 × 1012
Maximum3.7576182 × 1013
Range3.7381669 × 1013
Interquartile range (IQR)6.9554062 × 1011

Descriptive statistics

Standard deviation3.9492236 × 1012
Coefficient of variation (CV)2.3660667
Kurtosis55.899792
Mean1.6691092 × 1012
Median Absolute Deviation (MAD)2.9841808 × 1011
Skewness7.0375468
Sum4.5900503 × 1014
Variance1.5596367 × 1025
MonotonicityNot monotonic
2023-12-11T06:59:51.523060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
579149010894 1
 
0.4%
1265714877010 1
 
0.4%
1228638876849 1
 
0.4%
692440777626 1
 
0.4%
976248713922 1
 
0.4%
828643093289 1
 
0.4%
787779820360 1
 
0.4%
1353539880158 1
 
0.4%
972909734170 1
 
0.4%
551433941286 1
 
0.4%
Other values (265) 265
96.4%
ValueCountFrequency (%)
194513233070 1
0.4%
233159467258 1
0.4%
235040398810 1
0.4%
244842620617 1
0.4%
280519741334 1
0.4%
296425360675 1
0.4%
326019002186 1
0.4%
336390634603 1
0.4%
337686998011 1
0.4%
342078639911 1
0.4%
ValueCountFrequency (%)
37576182038200 1
0.4%
34986195317634 1
0.4%
32448415188425 1
0.4%
12880357626306 1
0.4%
11178825436109 1
0.4%
10852027395769 1
0.4%
10677722253775 1
0.4%
9593001746944 1
0.4%
9524288959769 1
0.4%
8014791116943 1
0.4%

Interactions

2023-12-11T06:59:49.682140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:59:51.648784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명수익총계액(원)
회계연도1.000NaN0.000
시군명NaN1.0001.000
수익총계액(원)0.0001.0001.000
2023-12-11T06:59:51.976027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수익총계액(원)회계연도
수익총계액(원)1.0000.000
회계연도0.0001.000

Missing values

2023-12-11T06:59:49.798764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:59:49.873942image/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

회계연도시군명자치단체명수익총계액(원)
02021가평군경기가평군579149010894
12021경기도경기본청34986195317634
22021고양시경기고양시2987386828631
32021과천시경기과천시506398540287
42021광명시경기광명시985116578742
52021광주시경기광주시1407693072198
62021구리시경기구리시713990074981
72021군포시경기군포시828044472509
82021김포시경기김포시1625418197336
92021남양주시경기남양주시2224274324596
회계연도시군명자치단체명수익총계액(원)
2652020<NA>대구중구326019002186
2662020<NA>대구동구885529525361
2672020<NA>대구서구528037032461
2682020<NA>대구남구492271216049
2692020<NA>대구북구945010567061
2702020<NA>대구수성구915487476051
2712020<NA>대구달성군883883691703
2722020<NA>인천본청11178825436109
2732020<NA>인천중구475440298313
2742020<NA>인천동구280519741334