Overview

Dataset statistics

Number of variables6
Number of observations243
Missing cells243
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory53.5 B

Variable types

Categorical1
Unsupported1
Text1
Numeric3

Dataset

Description맞춤형 복지비 비율 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=IU53RHZRYRJWS0N3LW3L22392766&infSeq=1

Alerts

회계연도 has constant value ""Constant
맞춤형복지비(원) is highly overall correlated with 세출결산액(원)High correlation
세출결산액(원) is highly overall correlated with 맞춤형복지비(원)High correlation
시군명 has 243 (100.0%) missing valuesMissing
자치단체명 has unique valuesUnique
맞춤형복지비(원) has unique valuesUnique
세출결산액(원) has unique valuesUnique
시군명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:35:50.904499
Analysis finished2023-12-10 22:35:51.932561
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2017
243 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 243
100.0%

Length

2023-12-11T07:35:51.983667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:35:52.058796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 243
100.0%

시군명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing243
Missing (%)100.0%
Memory size2.3 KiB

자치단체명
Text

UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-11T07:35:52.316644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.8559671
Min length4

Characters and Unicode

Total characters1180
Distinct characters131
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

Unique243 ?
Unique (%)100.0%

Sample

1st row부산본청
2nd row부산중구
3rd row부산서구
4th row부산동구
5th row부산영도구
ValueCountFrequency (%)
부산본청 1
 
0.4%
충남천안시 1
 
0.4%
전남영암군 1
 
0.4%
전남순천시 1
 
0.4%
전남나주시 1
 
0.4%
전남광양시 1
 
0.4%
전남담양군 1
 
0.4%
전남곡성군 1
 
0.4%
전남구례군 1
 
0.4%
전남고흥군 1
 
0.4%
Other values (233) 233
95.9%
2023-12-11T07:35:52.748390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 85
 
7.2%
구 83
 
7.0%
경 78
 
6.6%
시 76
 
6.4%
남 71
 
6.0%
북 57
 
4.8%
전 45
 
3.8%
산 39
 
3.3%
서 38
 
3.2%
울 35
 
3.0%
Other values (121) 573
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1180
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 85
 
7.2%
구 83
 
7.0%
경 78
 
6.6%
시 76
 
6.4%
남 71
 
6.0%
북 57
 
4.8%
전 45
 
3.8%
산 39
 
3.3%
서 38
 
3.2%
울 35
 
3.0%
Other values (121) 573
48.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1180
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 85
 
7.2%
구 83
 
7.0%
경 78
 
6.6%
시 76
 
6.4%
남 71
 
6.0%
북 57
 
4.8%
전 45
 
3.8%
산 39
 
3.3%
서 38
 
3.2%
울 35
 
3.0%
Other values (121) 573
48.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1180
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 85
 
7.2%
구 83
 
7.0%
경 78
 
6.6%
시 76
 
6.4%
남 71
 
6.0%
북 57
 
4.8%
전 45
 
3.8%
산 39
 
3.3%
서 38
 
3.2%
울 35
 
3.0%
Other values (121) 573
48.6%

맞춤형복지비(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0730206 × 109
Minimum3.142222 × 108
Maximum1.8828669 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T07:35:52.863413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.142222 × 108
5-th percentile6.9932243 × 108
Q19.4567298 × 108
median1.4359785 × 109
Q32.4532873 × 109
95-th percentile5.26 × 109
Maximum1.8828669 × 1010
Range1.8514447 × 1010
Interquartile range (IQR)1.5076143 × 109

Descriptive statistics

Standard deviation1.8802832 × 109
Coefficient of variation (CV)0.9070258
Kurtosis27.096271
Mean2.0730206 × 109
Median Absolute Deviation (MAD)5.8492572 × 108
Skewness3.9805376
Sum5.0374401 × 1011
Variance3.5354649 × 1018
MonotonicityNot monotonic
2023-12-11T07:35:52.975306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5295000000 1
 
0.4%
2690000000 1
 
0.4%
1370333000 1
 
0.4%
2383783310 1
 
0.4%
684370940 1
 
0.4%
986850000 1
 
0.4%
616593070 1
 
0.4%
1323816490 1
 
0.4%
895245670 1
 
0.4%
1723965230 1
 
0.4%
Other values (233) 233
95.9%
ValueCountFrequency (%)
314222200 1
0.4%
541620331 1
0.4%
584000000 1
0.4%
588738810 1
0.4%
616593070 1
0.4%
644051530 1
0.4%
662235380 1
0.4%
666900000 1
0.4%
678424280 1
0.4%
684370940 1
0.4%
ValueCountFrequency (%)
18828669000 1
0.4%
9746000000 1
0.4%
8574000000 1
0.4%
8178397070 1
0.4%
7655000000 1
0.4%
6356155000 1
0.4%
6225000000 1
0.4%
5959892340 1
0.4%
5940120800 1
0.4%
5556000000 1
0.4%

세출결산액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.8196192 × 1011
Minimum1.3207601 × 1011
Maximum2.2077574 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T07:35:53.085219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3207601 × 1011
5-th percentile2.4935989 × 1011
Q13.4439268 × 1011
median4.800335 × 1011
Q36.7145192 × 1011
95-th percentile3.8315045 × 1012
Maximum2.2077574 × 1013
Range2.1945498 × 1013
Interquartile range (IQR)3.2705925 × 1011

Descriptive statistics

Standard deviation2.1674021 × 1012
Coefficient of variation (CV)2.207216
Kurtosis58.041451
Mean9.8196192 × 1011
Median Absolute Deviation (MAD)1.466016 × 1011
Skewness6.9531631
Sum2.3861675 × 1014
Variance4.6976317 × 1024
MonotonicityNot monotonic
2023-12-11T07:35:53.191763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8342800808970 1
 
0.4%
913806866671 1
 
0.4%
679588457354 1
 
0.4%
589561252018 1
 
0.4%
327428405270 1
 
0.4%
303405265495 1
 
0.4%
258711359710 1
 
0.4%
558042498623 1
 
0.4%
390984073307 1
 
0.4%
440757574237 1
 
0.4%
Other values (233) 233
95.9%
ValueCountFrequency (%)
132076005930 1
0.4%
136262268376 1
0.4%
154493308348 1
0.4%
174951698090 1
0.4%
176199947714 1
0.4%
190126742870 1
0.4%
226549280940 1
0.4%
228656900351 1
0.4%
228847684689 1
0.4%
233439012402 1
0.4%
ValueCountFrequency (%)
22077574113882 1
0.4%
19245319155112 1
0.4%
8342800808970 1
0.4%
7220442102795 1
0.4%
7072272157276 1
0.4%
6562923172249 1
0.4%
6026021828735 1
0.4%
5376320950693 1
0.4%
5122011210719 1
0.4%
4987166484282 1
0.4%

맞춤형복지비비율(%)
Real number (ℝ)

Distinct65
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.32057613
Minimum0.03
Maximum0.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-11T07:35:53.298606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.151
Q10.23
median0.27
Q30.36
95-th percentile0.689
Maximum0.96
Range0.93
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.16043483
Coefficient of variation (CV)0.50045783
Kurtosis3.2314517
Mean0.32057613
Median Absolute Deviation (MAD)0.06
Skewness1.7094942
Sum77.9
Variance0.025739336
MonotonicityNot monotonic
2023-12-11T07:35:53.407382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.24 20
 
8.2%
0.25 17
 
7.0%
0.28 14
 
5.8%
0.26 14
 
5.8%
0.23 12
 
4.9%
0.27 12
 
4.9%
0.33 10
 
4.1%
0.22 8
 
3.3%
0.2 8
 
3.3%
0.29 8
 
3.3%
Other values (55) 120
49.4%
ValueCountFrequency (%)
0.03 1
 
0.4%
0.06 1
 
0.4%
0.07 1
 
0.4%
0.09 2
0.8%
0.1 1
 
0.4%
0.11 1
 
0.4%
0.12 4
1.6%
0.15 2
0.8%
0.16 3
1.2%
0.17 3
1.2%
ValueCountFrequency (%)
0.96 1
0.4%
0.95 1
0.4%
0.89 1
0.4%
0.87 1
0.4%
0.83 1
0.4%
0.81 1
0.4%
0.75 1
0.4%
0.73 1
0.4%
0.72 2
0.8%
0.71 1
0.4%

Interactions

2023-12-11T07:35:51.524418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.037862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.302717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.623851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.128752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.388570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.706934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.218269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:35:51.451920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:35:53.475377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
맞춤형복지비(원)세출결산액(원)맞춤형복지비비율(%)
맞춤형복지비(원)1.0000.7980.562
세출결산액(원)0.7981.0000.589
맞춤형복지비비율(%)0.5620.5891.000
2023-12-11T07:35:53.546631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
맞춤형복지비(원)세출결산액(원)맞춤형복지비비율(%)
맞춤형복지비(원)1.0000.7990.187
세출결산액(원)0.7991.000-0.332
맞춤형복지비비율(%)0.187-0.3321.000

Missing values

2023-12-11T07:35:51.809718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:35:51.897488image/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

회계연도시군명자치단체명맞춤형복지비(원)세출결산액(원)맞춤형복지비비율(%)
02017<NA>부산본청529500000083428008089700.06
12017<NA>부산중구9223049501320760059300.7
22017<NA>부산서구11146130802493563354300.45
32017<NA>부산동구10870660402265492809400.48
42017<NA>부산영도구11650000002620608793600.44
52017<NA>부산부산진구18403283404510549198500.41
62017<NA>부산동래구12665510603017498174200.42
72017<NA>부산남구14727269103384064409800.44
82017<NA>부산북구14108602203874375370900.36
92017<NA>부산해운대구18517740005115392096400.36
회계연도시군명자치단체명맞춤형복지비(원)세출결산액(원)맞춤형복지비비율(%)
2332017<NA>서울양천구36046848335541701673540.65
2342017<NA>서울강서구41590000006879838376900.6
2352017<NA>서울구로구29333183105336700682990.55
2362017<NA>서울금천구33133760103729318469900.89
2372017<NA>서울영등포구34447275254840326813770.71
2382017<NA>서울동작구35400000004820753723780.73
2392017<NA>서울관악구40077640005584818518570.72
2402017<NA>서울서초구43661040005398578782040.81
2412017<NA>서울송파구35055940006038995194170.58
2422017<NA>서울강동구36054658805438900191060.66