Overview

Dataset statistics

Number of variables10
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory90.3 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 체납액 규모별 체납건수를 납세자 유형별로 제공되는 것으로 과세연도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액 등으로 구성
Author경상남도 함양군
URLhttps://www.data.go.kr/data/15079375/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액 and 1 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액 and 1 other fieldsHigh correlation
체납액구간 is highly overall correlated with 체납금액 and 1 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:15:33.627853
Analysis finished2024-04-06 08:15:39.329362
Duration5.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
경상남도
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 31
100.0%

Length

2024-04-06T17:15:39.483580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:39.709222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 31
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
함양군
31 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양군 31
100.0%

Length

2024-04-06T17:15:39.914822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:40.095357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함양군 31
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
48870
31 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48870
2nd row48870
3rd row48870
4th row48870
5th row48870

Common Values

ValueCountFrequency (%)
48870 31
100.0%

Length

2024-04-06T17:15:40.292336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:40.462058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48870 31
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2022
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 31
100.0%

Length

2024-04-06T17:15:40.661689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:40.906356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 31
100.0%

세목명
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
재산세
9 
지방소득세
9 
취득세
5 
주민세
4 
자동차세
3 

Length

Max length5
Median length3
Mean length3.7419355
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 9
29.0%
지방소득세 9
29.0%
취득세 5
16.1%
주민세 4
12.9%
자동차세 3
 
9.7%
등록면허세 1
 
3.2%

Length

2024-04-06T17:15:41.115223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:41.343131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 9
29.0%
지방소득세 9
29.0%
취득세 5
16.1%
주민세 4
12.9%
자동차세 3
 
9.7%
등록면허세 1
 
3.2%

체납액구간
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
10만원 미만
6 
10만원~30만원미만
5 
30만원~50만원미만
5 
50만원~1백만원미만
4 
1백만원~3백만원미만
3 
Other values (5)
8 

Length

Max length11
Median length11
Mean length10.193548
Min length7

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row10만원 미만

Common Values

ValueCountFrequency (%)
10만원 미만 6
19.4%
10만원~30만원미만 5
16.1%
30만원~50만원미만 5
16.1%
50만원~1백만원미만 4
12.9%
1백만원~3백만원미만 3
9.7%
1천만원~3천만원미만 2
 
6.5%
3백만원~5백만원미만 2
 
6.5%
5백만원~1천만원미만 2
 
6.5%
5천만원~1억원미만 1
 
3.2%
3천만원~5천만원미만 1
 
3.2%

Length

2024-04-06T17:15:41.645266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:15:42.057779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 6
16.2%
미만 6
16.2%
10만원~30만원미만 5
13.5%
30만원~50만원미만 5
13.5%
50만원~1백만원미만 4
10.8%
1백만원~3백만원미만 3
8.1%
1천만원~3천만원미만 2
 
5.4%
3백만원~5백만원미만 2
 
5.4%
5백만원~1천만원미만 2
 
5.4%
5천만원~1억원미만 1
 
2.7%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.29032
Minimum1
Maximum1470
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T17:15:42.441450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median8
Q322
95-th percentile716.5
Maximum1470
Range1469
Interquartile range (IQR)20

Descriptive statistics

Standard deviation322.64792
Coefficient of variation (CV)2.7275935
Kurtosis12.459941
Mean118.29032
Median Absolute Deviation (MAD)7
Skewness3.5433839
Sum3667
Variance104101.68
MonotonicityNot monotonic
2024-04-06T17:15:42.723021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2 5
16.1%
1 4
12.9%
3 3
 
9.7%
9 3
 
9.7%
4 2
 
6.5%
18 2
 
6.5%
1080 1
 
3.2%
6 1
 
3.2%
8 1
 
3.2%
26 1
 
3.2%
Other values (8) 8
25.8%
ValueCountFrequency (%)
1 4
12.9%
2 5
16.1%
3 3
9.7%
4 2
 
6.5%
6 1
 
3.2%
8 1
 
3.2%
9 3
9.7%
16 1
 
3.2%
17 1
 
3.2%
18 2
 
6.5%
ValueCountFrequency (%)
1470 1
3.2%
1080 1
3.2%
353 1
3.2%
232 1
3.2%
165 1
3.2%
128 1
3.2%
72 1
3.2%
26 1
3.2%
18 2
6.5%
17 1
3.2%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16213634
Minimum271690
Maximum1.5486035 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T17:15:43.014143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum271690
5-th percentile527295
Q12798415
median6504660
Q318964125
95-th percentile37873310
Maximum1.5486035 × 108
Range1.5458866 × 108
Interquartile range (IQR)16165710

Descriptive statistics

Standard deviation28178084
Coefficient of variation (CV)1.7379253
Kurtosis20.617134
Mean16213634
Median Absolute Deviation (MAD)5955200
Skewness4.2264797
Sum5.0262264 × 108
Variance7.9400442 × 1014
MonotonicityNot monotonic
2024-04-06T17:15:43.326396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2664660 1
 
3.2%
13697150 1
 
3.2%
2208200 1
 
3.2%
811970 1
 
3.2%
3289110 1
 
3.2%
505130 1
 
3.2%
271690 1
 
3.2%
26842730 1
 
3.2%
6504660 1
 
3.2%
30441920 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
271690 1
3.2%
505130 1
3.2%
549460 1
3.2%
811970 1
3.2%
1474270 1
3.2%
1517860 1
3.2%
2208200 1
3.2%
2664660 1
3.2%
2932170 1
3.2%
3289110 1
3.2%
ValueCountFrequency (%)
154860350 1
3.2%
39600600 1
3.2%
36146020 1
3.2%
31797910 1
3.2%
30441920 1
3.2%
26842730 1
3.2%
24243050 1
3.2%
21362990 1
3.2%
16565260 1
3.2%
14471570 1
3.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299.35484
Minimum2
Maximum3944
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T17:15:43.681591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.5
Q19
median18
Q354.5
95-th percentile1656.5
Maximum3944
Range3942
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation821.18165
Coefficient of variation (CV)2.7431715
Kurtosis14.169173
Mean299.35484
Median Absolute Deviation (MAD)13
Skewness3.6813937
Sum9280
Variance674339.3
MonotonicityNot monotonic
2024-04-06T17:15:44.069143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
9 3
 
9.7%
5 3
 
9.7%
22 2
 
6.5%
2 2
 
6.5%
15 2
 
6.5%
12 2
 
6.5%
323 1
 
3.2%
139 1
 
3.2%
6 1
 
3.2%
18 1
 
3.2%
Other values (13) 13
41.9%
ValueCountFrequency (%)
2 2
6.5%
3 1
 
3.2%
5 3
9.7%
6 1
 
3.2%
9 3
9.7%
11 1
 
3.2%
12 2
6.5%
15 2
6.5%
18 1
 
3.2%
22 2
6.5%
ValueCountFrequency (%)
3944 1
3.2%
2373 1
3.2%
940 1
3.2%
847 1
3.2%
323 1
3.2%
290 1
3.2%
139 1
3.2%
58 1
3.2%
51 1
3.2%
45 1
3.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66104495
Minimum811970
Maximum9.1951046 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-06T17:15:44.391933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum811970
5-th percentile1438150
Q16278890
median19709240
Q347824235
95-th percentile2.1099568 × 108
Maximum9.1951046 × 108
Range9.1869849 × 108
Interquartile range (IQR)41545345

Descriptive statistics

Standard deviation1.6741742 × 108
Coefficient of variation (CV)2.5326178
Kurtosis24.286165
Mean66104495
Median Absolute Deviation (MAD)15363320
Skewness4.7687311
Sum2.0492394 × 109
Variance2.8028593 × 1016
MonotonicityNot monotonic
2024-04-06T17:15:44.635490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5239260 1
 
3.2%
40041420 1
 
3.2%
6866760 1
 
3.2%
811970 1
 
3.2%
10593440 1
 
3.2%
4345920 1
 
3.2%
972070 1
 
3.2%
68435950 1
 
3.2%
15833550 1
 
3.2%
67732410 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
811970 1
3.2%
972070 1
3.2%
1904230 1
3.2%
2077550 1
3.2%
4345920 1
3.2%
5104960 1
3.2%
5239260 1
3.2%
5719650 1
3.2%
6838130 1
3.2%
6866760 1
3.2%
ValueCountFrequency (%)
919510460 1
3.2%
277640170 1
3.2%
144351200 1
3.2%
72605710 1
3.2%
68435950 1
3.2%
68187930 1
3.2%
67732410 1
3.2%
48744770 1
3.2%
46903700 1
3.2%
45409700 1
3.2%

Interactions

2024-04-06T17:15:37.977594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:34.458046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:35.561882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.466261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.202185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:34.751102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:35.768749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.698237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.405332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:35.051630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:35.970937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.456132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:38.596035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:35.298177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:36.159321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:37.741119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:15:44.859026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.5710.0000.5950.000
체납액구간0.0001.0000.0000.8040.0000.781
체납건수0.5710.0001.0000.2250.9310.230
체납금액0.0000.8040.2251.0000.5750.951
누적체납건수0.5950.0000.9310.5751.0000.592
누적체납금액0.0000.7810.2300.9510.5921.000
2024-04-06T17:15:45.039756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2024-04-06T17:15:45.195784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.1800.9090.0280.4180.000
체납금액0.1801.0000.2470.9520.0000.554
누적체납건수0.9090.2471.0000.1730.4050.000
누적체납금액0.0280.9520.1731.0000.0000.528
세목명0.4180.0000.4050.0001.0000.000
체납액구간0.0000.5540.0000.5280.0001.000

Missing values

2024-04-06T17:15:38.920919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:15:39.230306image/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
0경상남도함양군488702022등록면허세10만원 미만16526646603235239260
1경상남도함양군488702022자동차세10만원 미만3531369715094040041420
2경상남도함양군488702022자동차세10만원~30만원미만23239600600847144351200
3경상남도함양군488702022자동차세30만원~50만원미만1757116905819709240
4경상남도함양군488702022재산세10만원 미만147031797910394472605710
5경상남도함양군488702022재산세10만원~30만원미만1282136299029048744770
6경상남도함양군488702022재산세1백만원~3백만원미만16242430504568187930
7경상남도함양군488702022재산세1천만원~3천만원미만23614602015277640170
8경상남도함양군488702022재산세30만원~50만원미만1866120202810471390
9경상남도함양군488702022재산세3백만원~5백만원미만310792730518562170
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
21경상남도함양군488702022지방소득세30만원~50만원미만93532080155719650
22경상남도함양군488702022지방소득세3백만원~5백만원미만26455210934258160
23경상남도함양군488702022지방소득세3천만원~5천만원미만130441920267732410
24경상남도함양군488702022지방소득세50만원~1백만원미만965046602215833550
25경상남도함양군488702022지방소득세5백만원~1천만원미만426842730968435950
26경상남도함양군488702022취득세10만원 미만627169018972070
27경상남도함양군488702022취득세10만원~30만원미만3505130224345920
28경상남도함양군488702022취득세1백만원~3백만원미만23289110610593440
29경상남도함양군488702022취득세30만원~50만원미만28119702811970
30경상남도함양군488702022취득세50만원~1백만원미만3220820096866760