Overview

Dataset statistics

Number of variables10
Number of observations224
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.9 KiB
Average record size in memory86.6 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별로 제공하는 데이터로 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 체납액구간, 체납건수, 체납금액 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079616

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
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
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:40:35.413691
Analysis finished2023-12-11 00:40:37.494048
Duration2.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경상남도
224 

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 224
100.0%

Length

2023-12-11T09:40:37.577953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:40:37.701177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 224
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
김해시
224 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해시 224
100.0%

Length

2023-12-11T09:40:37.790511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:40:37.883883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해시 224
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
48250
224 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48250
2nd row48250
3rd row48250
4th row48250
5th row48250

Common Values

ValueCountFrequency (%)
48250 224
100.0%

Length

2023-12-11T09:40:38.000153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:40:38.121961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48250 224
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2019
47 
2020
47 
2018
45 
2021
44 
2017
41 

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 (%)
2019 47
21.0%
2020 47
21.0%
2018 45
20.1%
2021 44
19.6%
2017 41
18.3%

Length

2023-12-11T09:40:38.274026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:40:38.398557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 47
21.0%
2020 47
21.0%
2018 45
20.1%
2021 44
19.6%
2017 41
18.3%

세목명
Categorical

Distinct7
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
취득세
54 
지방소득세
51 
재산세
45 
주민세
29 
자동차세
20 
Other values (2)
25 

Length

Max length7
Median length3
Mean length3.9375
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취득세 54
24.1%
지방소득세 51
22.8%
재산세 45
20.1%
주민세 29
12.9%
자동차세 20
 
8.9%
지역자원시설세 19
 
8.5%
등록면허세 6
 
2.7%

Length

2023-12-11T09:40:38.534833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:40:38.686402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취득세 54
24.1%
지방소득세 51
22.8%
재산세 45
20.1%
주민세 29
12.9%
자동차세 20
 
8.9%
지역자원시설세 19
 
8.5%
등록면허세 6
 
2.7%

체납액구간
Categorical

Distinct13
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
10만원 미만
35 
10만원~30만원미만
31 
30만원~50만원미만
28 
50만원~1백만원미만
27 
1백만원~3백만원미만
22 
Other values (8)
81 

Length

Max length11
Median length11
Mean length10.276786
Min length7

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 35
15.6%
10만원~30만원미만 31
13.8%
30만원~50만원미만 28
12.5%
50만원~1백만원미만 27
12.1%
1백만원~3백만원미만 22
9.8%
3백만원~5백만원미만 20
8.9%
1천만원~3천만원미만 16
7.1%
5백만원~1천만원미만 15
6.7%
3천만원~5천만원미만 14
 
6.2%
5천만원~1억원미만 9
 
4.0%
Other values (3) 7
 
3.1%

Length

2023-12-11T09:40:38.854239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
13.5%
미만 35
13.5%
10만원~30만원미만 31
12.0%
30만원~50만원미만 28
10.8%
50만원~1백만원미만 27
10.4%
1백만원~3백만원미만 22
8.5%
3백만원~5백만원미만 20
7.7%
1천만원~3천만원미만 16
6.2%
5백만원~1천만원미만 15
5.8%
3천만원~5천만원미만 14
 
5.4%
Other values (4) 16
6.2%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct132
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1019.0357
Minimum1
Maximum25134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-11T09:40:38.985176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17.75
median35
Q3261.75
95-th percentile6887.4
Maximum25134
Range25133
Interquartile range (IQR)254

Descriptive statistics

Standard deviation3147.5512
Coefficient of variation (CV)3.0887546
Kurtosis31.088568
Mean1019.0357
Median Absolute Deviation (MAD)33
Skewness5.0362357
Sum228264
Variance9907078.9
MonotonicityNot monotonic
2023-12-11T09:40:39.124689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 21
 
9.4%
2 9
 
4.0%
4 8
 
3.6%
3 7
 
3.1%
5 7
 
3.1%
9 5
 
2.2%
8 5
 
2.2%
11 5
 
2.2%
15 5
 
2.2%
10 3
 
1.3%
Other values (122) 149
66.5%
ValueCountFrequency (%)
1 21
9.4%
2 9
4.0%
3 7
 
3.1%
4 8
 
3.6%
5 7
 
3.1%
6 2
 
0.9%
7 2
 
0.9%
8 5
 
2.2%
9 5
 
2.2%
10 3
 
1.3%
ValueCountFrequency (%)
25134 1
0.4%
24776 1
0.4%
14250 1
0.4%
11124 1
0.4%
10095 1
0.4%
9143 1
0.4%
9058 1
0.4%
8753 1
0.4%
7920 1
0.4%
7687 1
0.4%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7210277 × 108
Minimum210120
Maximum1.51176 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-11T09:40:39.247412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210120
5-th percentile1116509.5
Q113669398
median85230945
Q32.3674821 × 108
95-th percentile5.8356293 × 108
Maximum1.51176 × 109
Range1.5115499 × 109
Interquartile range (IQR)2.2307882 × 108

Descriptive statistics

Standard deviation2.45518 × 108
Coefficient of variation (CV)1.4265779
Kurtosis8.7173412
Mean1.7210277 × 108
Median Absolute Deviation (MAD)79607170
Skewness2.661076
Sum3.855102 × 1010
Variance6.0279088 × 1016
MonotonicityNot monotonic
2023-12-11T09:40:39.689281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9327760 1
 
0.4%
180613770 1
 
0.4%
564894200 1
 
0.4%
139258800 1
 
0.4%
381686940 1
 
0.4%
484891860 1
 
0.4%
339004330 1
 
0.4%
57414780 1
 
0.4%
20184710 1
 
0.4%
12342100 1
 
0.4%
Other values (214) 214
95.5%
ValueCountFrequency (%)
210120 1
0.4%
297770 1
0.4%
306830 1
0.4%
331580 1
0.4%
387390 1
0.4%
423140 1
0.4%
558210 1
0.4%
628340 1
0.4%
862060 1
0.4%
880450 1
0.4%
ValueCountFrequency (%)
1511760000 1
0.4%
1336893810 1
0.4%
1310541920 1
0.4%
1060765480 1
0.4%
963871700 1
0.4%
958157370 1
0.4%
924186380 1
0.4%
845456100 1
0.4%
787195270 1
0.4%
749113270 1
0.4%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct172
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3687.5089
Minimum1
Maximum75266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-11T09:40:39.833544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q123.75
median139
Q3858.5
95-th percentile26979.95
Maximum75266
Range75265
Interquartile range (IQR)834.75

Descriptive statistics

Standard deviation11172.516
Coefficient of variation (CV)3.0298276
Kurtosis18.353933
Mean3687.5089
Median Absolute Deviation (MAD)133
Skewness4.0859248
Sum826002
Variance1.2482512 × 108
MonotonicityNot monotonic
2023-12-11T09:40:39.963368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
4.5%
2 6
 
2.7%
4 5
 
2.2%
13 4
 
1.8%
7 3
 
1.3%
5 3
 
1.3%
19 3
 
1.3%
9 3
 
1.3%
3 3
 
1.3%
162 2
 
0.9%
Other values (162) 182
81.2%
ValueCountFrequency (%)
1 10
4.5%
2 6
2.7%
3 3
 
1.3%
4 5
2.2%
5 3
 
1.3%
6 2
 
0.9%
7 3
 
1.3%
9 3
 
1.3%
10 1
 
0.4%
11 1
 
0.4%
ValueCountFrequency (%)
75266 1
0.4%
74864 1
0.4%
50132 1
0.4%
46843 1
0.4%
45553 1
0.4%
43760 1
0.4%
42427 1
0.4%
35882 1
0.4%
34740 1
0.4%
34617 1
0.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4773714 × 108
Minimum306830
Maximum7.4426092 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-11T09:40:40.089674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum306830
5-th percentile3349646.5
Q173888832
median2.1836866 × 108
Q37.0682458 × 108
95-th percentile1.8455269 × 109
Maximum7.4426092 × 109
Range7.4423023 × 109
Interquartile range (IQR)6.3293574 × 108

Descriptive statistics

Standard deviation9.4363899 × 108
Coefficient of variation (CV)1.7227953
Kurtosis25.579415
Mean5.4773714 × 108
Median Absolute Deviation (MAD)2.0062728 × 108
Skewness4.4553504
Sum1.2269312 × 1011
Variance8.9045454 × 1017
MonotonicityNot monotonic
2023-12-11T09:40:40.237948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23282660 1
 
0.4%
680804650 1
 
0.4%
1182317960 1
 
0.4%
253960900 1
 
0.4%
723806090 1
 
0.4%
1193256770 1
 
0.4%
1105328310 1
 
0.4%
142506710 1
 
0.4%
210395720 1
 
0.4%
12342100 1
 
0.4%
Other values (214) 214
95.5%
ValueCountFrequency (%)
306830 1
0.4%
423140 1
0.4%
490280 1
0.4%
638410 1
0.4%
720910 1
0.4%
880450 1
0.4%
1053280 1
0.4%
1438660 1
0.4%
1582970 1
0.4%
2194230 1
0.4%
ValueCountFrequency (%)
7442609160 1
0.4%
6954579940 1
0.4%
5644038020 1
0.4%
4132278020 1
0.4%
3174120650 1
0.4%
3014206540 1
0.4%
2430635060 1
0.4%
2115329280 1
0.4%
2093762010 1
0.4%
2001991130 1
0.4%

Interactions

2023-12-11T09:40:36.870376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:35.739417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.105501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.516691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.951220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:35.835486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.201414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.595739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:37.051431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:35.922569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.317734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.687984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:37.151497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.008582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.423648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:40:36.773592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:40:40.359934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.2180.0990.225
세목명0.0001.0000.2380.5270.3070.3780.301
체납액구간0.0000.2381.0000.2640.5390.0000.098
체납건수0.0000.5270.2641.0000.6460.9060.612
체납금액0.2180.3070.5390.6461.0000.6710.888
누적체납건수0.0990.3780.0000.9060.6711.0000.818
누적체납금액0.2250.3010.0980.6120.8880.8181.000
2023-12-11T09:40:40.481388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간과세년도세목명
체납액구간1.0000.0000.110
과세년도0.0001.0000.000
세목명0.1100.0001.000
2023-12-11T09:40:40.589461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4080.9790.4320.0000.2070.123
체납금액0.4081.0000.3280.9610.0880.1600.254
누적체납건수0.9790.3281.0000.3900.0590.2120.000
누적체납금액0.4320.9610.3901.0000.1380.1660.045
과세년도0.0000.0880.0590.1381.0000.0000.000
세목명0.2070.1600.2120.1660.0001.0000.110
체납액구간0.1230.2540.0000.0450.0000.1101.000

Missing values

2023-12-11T09:40:37.284719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:40:37.434185image/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
0경상남도김해시482502017등록면허세10만원 미만5609327760145923282660
1경상남도김해시482502017자동차세10만원 미만4145192981700223591008524550
2경상남도김해시482502017자동차세10만원~30만원미만4663749113270197633174120650
3경상남도김해시482502017자동차세30만원~50만원미만15051110140552188184680
4경상남도김해시482502017자동차세50만원~1백만원미만211198733010467519030
5경상남도김해시482502017재산세10만원 미만3534935890309372272092390
6경상남도김해시482502017재산세10만원~30만원미만456667199401332203289540
7경상남도김해시482502017재산세1백만원~3백만원미만5391892690178290635760
8경상남도김해시482502017재산세1천만원~3천만원미만34697998011145372550
9경상남도김해시482502017재산세30만원~50만원미만532034976021179480770
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
214경상남도김해시482502021취득세10만원~30만원미만601119381021839453120
215경상남도김해시482502021취득세1백만원~3백만원미만2445186070109187364500
216경상남도김해시482502021취득세1억원~3억원미만111578002091123965660
217경상남도김해시482502021취득세1천만원~3천만원미만1323723473041781133710
218경상남도김해시482502021취득세30만원~50만원미만2080925105322114710
219경상남도김해시482502021취득세3백만원~5백만원미만93475582041163755190
220경상남도김해시482502021취득세3천만원~5천만원미만310116469019740677200
221경상남도김해시482502021취득세50만원~1백만원미만352335297012284179520
222경상남도김해시482502021취득세5백만원~1천만원미만128620737039269425150
223경상남도김해시482502021취득세5억원~10억원미만17871952701787195270