Overview

Dataset statistics

Number of variables10
Number of observations196
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory86.7 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 체납현황을 체납액 규모별로 제공
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078700

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:39:56.851091
Analysis finished2023-12-10 23:39:59.137874
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
창원시
196 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 196
100.0%

Length

2023-12-11T08:39:59.184963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:59.265220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 196
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
의창구
43 
성산구
41 
진해구
38 
마산합포구
37 
마산회원구
37 

Length

Max length5
Median length3
Mean length3.755102
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의창구
2nd row성산구
3rd row마산합포구
4th row마산회원구
5th row진해구

Common Values

ValueCountFrequency (%)
의창구 43
21.9%
성산구 41
20.9%
진해구 38
19.4%
마산합포구 37
18.9%
마산회원구 37
18.9%

Length

2023-12-11T08:39:59.349581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:59.444810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의창구 43
21.9%
성산구 41
20.9%
진해구 38
19.4%
마산합포구 37
18.9%
마산회원구 37
18.9%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
48121
43 
48123
41 
48129
38 
48125
37 
48127
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48121
2nd row48123
3rd row48125
4th row48127
5th row48129

Common Values

ValueCountFrequency (%)
48121 43
21.9%
48123 41
20.9%
48129 38
19.4%
48125 37
18.9%
48127 37
18.9%

Length

2023-12-11T08:39:59.536442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:59.623369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48121 43
21.9%
48123 41
20.9%
48129 38
19.4%
48125 37
18.9%
48127 37
18.9%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2021
196 

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 (%)
2021 196
100.0%

Length

2023-12-11T08:39:59.709141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:59.783070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 196
100.0%

세목명
Categorical

Distinct7
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
지방소득세
50 
재산세
47 
취득세
36 
주민세
28 
자동차세
18 
Other values (2)
17 

Length

Max length7
Median length3
Mean length3.8877551
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 50
25.5%
재산세 47
24.0%
취득세 36
18.4%
주민세 28
14.3%
자동차세 18
 
9.2%
지역자원시설세 11
 
5.6%
등록면허세 6
 
3.1%

Length

2023-12-11T08:39:59.865302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:39:59.957283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 50
25.5%
재산세 47
24.0%
취득세 36
18.4%
주민세 28
14.3%
자동차세 18
 
9.2%
지역자원시설세 11
 
5.6%
등록면허세 6
 
3.1%

체납액구간
Categorical

Distinct12
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
10만원 미만
35 
10만원~30만원미만
29 
30만원~50만원미만
27 
50만원~1백만원미만
22 
1백만원~3백만원미만
19 
Other values (7)
64 

Length

Max length11
Median length11
Mean length10.193878
Min length7

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원 미만
4th row10만원 미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 35
17.9%
10만원~30만원미만 29
14.8%
30만원~50만원미만 27
13.8%
50만원~1백만원미만 22
11.2%
1백만원~3백만원미만 19
9.7%
3백만원~5백만원미만 15
7.7%
5백만원~1천만원미만 14
 
7.1%
1천만원~3천만원미만 13
 
6.6%
3천만원~5천만원미만 9
 
4.6%
5천만원~1억원미만 8
 
4.1%
Other values (2) 5
 
2.6%

Length

2023-12-11T08:40:00.094229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
15.2%
미만 35
15.2%
10만원~30만원미만 29
12.6%
30만원~50만원미만 27
11.7%
50만원~1백만원미만 22
9.5%
1백만원~3백만원미만 19
8.2%
3백만원~5백만원미만 15
6.5%
5백만원~1천만원미만 14
 
6.1%
1천만원~3천만원미만 13
 
5.6%
3천만원~5천만원미만 9
 
3.9%
Other values (3) 13
 
5.6%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean506.87755
Minimum1
Maximum11267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:00.216126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median14
Q3105.25
95-th percentile2605
Maximum11267
Range11266
Interquartile range (IQR)102.25

Descriptive statistics

Standard deviation1515.2517
Coefficient of variation (CV)2.9893841
Kurtosis23.920039
Mean506.87755
Median Absolute Deviation (MAD)13
Skewness4.6266131
Sum99348
Variance2295987.7
MonotonicityNot monotonic
2023-12-11T08:40:00.321232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 29
 
14.8%
2 17
 
8.7%
3 9
 
4.6%
5 7
 
3.6%
7 7
 
3.6%
4 6
 
3.1%
9 5
 
2.6%
12 4
 
2.0%
10 3
 
1.5%
14 3
 
1.5%
Other values (90) 106
54.1%
ValueCountFrequency (%)
1 29
14.8%
2 17
8.7%
3 9
 
4.6%
4 6
 
3.1%
5 7
 
3.6%
6 3
 
1.5%
7 7
 
3.6%
8 2
 
1.0%
9 5
 
2.6%
10 3
 
1.5%
ValueCountFrequency (%)
11267 1
0.5%
8604 1
0.5%
8299 1
0.5%
7719 1
0.5%
7468 1
0.5%
4067 1
0.5%
3390 1
0.5%
3260 1
0.5%
3122 1
0.5%
2719 1
0.5%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct196
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72902247
Minimum206490
Maximum6.2049593 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:00.431330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206490
5-th percentile571750
Q15013130
median40090545
Q395743032
95-th percentile2.661895 × 108
Maximum6.2049593 × 108
Range6.2028944 × 108
Interquartile range (IQR)90729902

Descriptive statistics

Standard deviation98287260
Coefficient of variation (CV)1.3482062
Kurtosis9.0614572
Mean72902247
Median Absolute Deviation (MAD)38432935
Skewness2.6405705
Sum1.428884 × 1010
Variance9.6603854 × 1015
MonotonicityNot monotonic
2023-12-11T08:40:00.548872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22797240 1
 
0.5%
24746980 1
 
0.5%
108944310 1
 
0.5%
75393010 1
 
0.5%
62413230 1
 
0.5%
78710300 1
 
0.5%
67805880 1
 
0.5%
414938900 1
 
0.5%
121986650 1
 
0.5%
72644280 1
 
0.5%
Other values (186) 186
94.9%
ValueCountFrequency (%)
206490 1
0.5%
265320 1
0.5%
284000 1
0.5%
309920 1
0.5%
335420 1
0.5%
370800 1
0.5%
478980 1
0.5%
479950 1
0.5%
517250 1
0.5%
566440 1
0.5%
ValueCountFrequency (%)
620495930 1
0.5%
559511680 1
0.5%
464960910 1
0.5%
414938900 1
0.5%
378043060 1
0.5%
339360040 1
0.5%
304669130 1
0.5%
296876620 1
0.5%
288434020 1
0.5%
281791860 1
0.5%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8743.3163
Minimum1
Maximum131098
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:00.682521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q189
median347
Q32033
95-th percentile53760
Maximum131098
Range131097
Interquartile range (IQR)1944

Descriptive statistics

Standard deviation24213.173
Coefficient of variation (CV)2.7693351
Kurtosis15.112306
Mean8743.3163
Median Absolute Deviation (MAD)337
Skewness3.7788935
Sum1713690
Variance5.8627773 × 108
MonotonicityNot monotonic
2023-12-11T08:40:00.808249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
7984 5
 
2.6%
700 5
 
2.6%
310 5
 
2.6%
347 5
 
2.6%
5 5
 
2.6%
723 5
 
2.6%
493 5
 
2.6%
1892 5
 
2.6%
560 5
 
2.6%
1048 5
 
2.6%
Other values (36) 146
74.5%
ValueCountFrequency (%)
1 1
 
0.5%
2 2
 
1.0%
5 5
2.6%
9 4
2.0%
10 2
 
1.0%
11 3
1.5%
15 2
 
1.0%
17 2
 
1.0%
28 3
1.5%
31 3
1.5%
ValueCountFrequency (%)
131098 5
2.6%
59985 5
2.6%
51685 5
2.6%
43629 5
2.6%
16765 5
2.6%
10888 5
2.6%
7984 5
2.6%
3866 5
2.6%
2325 5
2.6%
2033 5
2.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2640491 × 109
Minimum676710
Maximum1.0065299 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:00.923713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum676710
5-th percentile12138590
Q11.584598 × 108
median7.0942309 × 108
Q31.7951927 × 109
95-th percentile3.7280801 × 109
Maximum1.0065299 × 1010
Range1.0064622 × 1010
Interquartile range (IQR)1.6367329 × 109

Descriptive statistics

Standard deviation1.8024496 × 109
Coefficient of variation (CV)1.4259332
Kurtosis12.445579
Mean1.2640491 × 109
Median Absolute Deviation (MAD)6.1039302 × 108
Skewness3.168664
Sum2.4775363 × 1011
Variance3.2488247 × 1018
MonotonicityNot monotonic
2023-12-11T08:40:01.040540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
239267530 5
 
2.6%
2155656350 5
 
2.6%
57296550 5
 
2.6%
14764410 5
 
2.6%
12138590 5
 
2.6%
3442296880 5
 
2.6%
1344443830 5
 
2.6%
2145369980 5
 
2.6%
420219830 5
 
2.6%
4424353170 5
 
2.6%
Other values (40) 146
74.5%
ValueCountFrequency (%)
676710 1
 
0.5%
2105200 2
 
1.0%
9989980 4
2.0%
12138590 5
2.6%
14764410 5
2.6%
23944820 4
2.0%
33416120 5
2.6%
57296550 5
2.6%
60106160 1
 
0.5%
60902120 2
 
1.0%
ValueCountFrequency (%)
10065299000 5
2.6%
4424353170 5
2.6%
3495989100 5
2.6%
3442296880 5
2.6%
2743354610 5
2.6%
2360349370 5
2.6%
2261397050 2
 
1.0%
2155656350 5
2.6%
2145369980 5
2.6%
1977291990 3
1.5%

Interactions

2023-12-11T08:39:58.598495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.235028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.600175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.223905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.676147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.335521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.927003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.329598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.755873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.421766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.033994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.420978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.851744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:57.505822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.138048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:39:58.513841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:40:01.126684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명체납액구간체납건수체납금액누적체납건수누적체납금액
시군구명1.0001.0000.0000.0000.0000.1240.0000.000
자치단체코드1.0001.0000.0000.0000.0000.1240.0000.000
세목명0.0000.0001.0000.1580.5570.3030.5260.563
체납액구간0.0000.0000.1581.0000.2190.5960.5570.787
체납건수0.0000.0000.5570.2191.0000.5890.8230.537
체납금액0.1240.1240.3030.5960.5891.0000.7130.743
누적체납건수0.0000.0000.5260.5570.8230.7131.0000.746
누적체납금액0.0000.0000.5630.7870.5370.7430.7461.000
2023-12-11T08:40:01.216543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드체납액구간세목명
시군구명1.0001.0000.0000.000
자치단체코드1.0001.0000.0000.000
체납액구간0.0000.0001.0000.074
세목명0.0000.0000.0741.000
2023-12-11T08:40:01.294615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액시군구명자치단체코드세목명체납액구간
체납건수1.0000.4250.9430.4380.0000.0000.2220.105
체납금액0.4251.0000.3190.8980.0720.0720.1650.300
누적체납건수0.9430.3191.0000.4270.0000.0000.3700.342
누적체납금액0.4380.8980.4271.0000.0000.0000.3780.424
시군구명0.0000.0720.0000.0001.0001.0000.0000.000
자치단체코드0.0000.0720.0000.0001.0001.0000.0000.000
세목명0.2220.1650.3700.3780.0000.0001.0000.074
체납액구간0.1050.3000.3420.4240.0000.0000.0741.000

Missing values

2023-12-11T08:39:58.974653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:39:59.093242image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0창원시의창구481212021등록면허세10만원 미만782227972407984239267530
1창원시성산구481232021등록면허세10만원 미만613226965607984239267530
2창원시마산합포구481252021등록면허세10만원 미만607172841507984239267530
3창원시마산회원구481272021등록면허세10만원 미만455123403207984239267530
4창원시진해구481292021등록면허세10만원 미만490166765207984239267530
5창원시의창구481212021등록면허세30만원~50만원미만13708002676710
6창원시의창구481212021자동차세10만원 미만3390150298770516852360349370
7창원시성산구481232021자동차세10만원 미만162275152890516852360349370
8창원시마산합포구481252021자동차세10만원 미만213896788900516852360349370
9창원시마산회원구481272021자동차세10만원 미만201488668910516852360349370
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
186창원시마산회원구481272021취득세3천만원~5천만원미만28428739010387039580
187창원시의창구481212021취득세50만원~1백만원미만107908900176130331520
188창원시마산합포구481252021취득세50만원~1백만원미만1828890176130331520
189창원시마산회원구481272021취득세50만원~1백만원미만21697690176130331520
190창원시진해구481292021취득세50만원~1백만원미만96743260176130331520
191창원시의창구481212021취득세5백만원~1천만원미만42487381057399335110
192창원시성산구481232021취득세5백만원~1천만원미만64395588057399335110
193창원시진해구481292021취득세5백만원~1천만원미만21911365057399335110
194창원시마산합포구481252021취득세5천만원~1억원미만1794762005365860580
195창원시마산회원구481272021취득세5천만원~1억원미만1803537605365860580