Overview

Dataset statistics

Number of variables10
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory87.7 B

Variable types

Categorical6
Numeric4

Dataset

Description경기도 안산시 체납액 규모별 체납 건수를 납세자 유형별로 체납액 구간에 따라 체납건수, 체납금액, 누적 체납건수, 누적 체납금액으로 구분하여 제공합니다.
URLhttps://www.data.go.kr/data/15080168/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 14:39:17.925290
Analysis finished2023-12-12 14:39:20.630254
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
경기도
80 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 80
100.0%

Length

2023-12-12T23:39:20.712098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:39:20.822973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 80
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
안산시 단원구
44 
안산시 상록구
36 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안산시 상록구
2nd row안산시 단원구
3rd row안산시 단원구
4th row안산시 상록구
5th row안산시 단원구

Common Values

ValueCountFrequency (%)
안산시 단원구 44
55.0%
안산시 상록구 36
45.0%

Length

2023-12-12T23:39:20.939970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:39:21.049186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안산시 80
50.0%
단원구 44
27.5%
상록구 36
22.5%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
41273
44 
41271
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41271
2nd row41273
3rd row41273
4th row41271
5th row41273

Common Values

ValueCountFrequency (%)
41273 44
55.0%
41271 36
45.0%

Length

2023-12-12T23:39:21.148972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:39:21.276032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41273 44
55.0%
41271 36
45.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
2022
80 

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 80
100.0%

Length

2023-12-12T23:39:21.388640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:39:21.494321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 80
100.0%

세목명
Categorical

Distinct7
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size772.0 B
지방소득세
24 
재산세
18 
취득세
15 
주민세
11 
자동차세
8 
Other values (2)
4 

Length

Max length7
Median length3
Mean length3.825
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 24
30.0%
재산세 18
22.5%
취득세 15
18.8%
주민세 11
13.8%
자동차세 8
 
10.0%
등록면허세 3
 
3.8%
지역자원시설세 1
 
1.2%

Length

2023-12-12T23:39:21.634036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:39:21.783120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 24
30.0%
재산세 18
22.5%
취득세 15
18.8%
주민세 11
13.8%
자동차세 8
 
10.0%
등록면허세 3
 
3.8%
지역자원시설세 1
 
1.2%

체납액구간
Categorical

Distinct13
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
10만원 미만
13 
10만원~30만원미만
11 
30만원~50만원미만
10 
50만원~1백만원미만
10 
1백만원~3백만원미만
8 
Other values (8)
28 

Length

Max length11
Median length11
Mean length10.225
Min length7

Unique

Unique2 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 13
16.2%
10만원~30만원미만 11
13.8%
30만원~50만원미만 10
12.5%
50만원~1백만원미만 10
12.5%
1백만원~3백만원미만 8
10.0%
3백만원~5백만원미만 7
8.8%
5백만원~1천만원미만 6
7.5%
1천만원~3천만원미만 5
 
6.2%
3천만원~5천만원미만 3
 
3.8%
5천만원~1억원미만 3
 
3.8%
Other values (3) 4
 
5.0%

Length

2023-12-12T23:39:21.942400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 13
14.0%
미만 13
14.0%
10만원~30만원미만 11
11.8%
30만원~50만원미만 10
10.8%
50만원~1백만원미만 10
10.8%
1백만원~3백만원미만 8
8.6%
3백만원~5백만원미만 7
7.5%
5백만원~1천만원미만 6
6.5%
1천만원~3천만원미만 5
 
5.4%
3천만원~5천만원미만 3
 
3.2%
Other values (4) 7
7.5%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1200.6875
Minimum1
Maximum27664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T23:39:22.139782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median34
Q3303.25
95-th percentile4547.4
Maximum27664
Range27663
Interquartile range (IQR)298.25

Descriptive statistics

Standard deviation4014.8873
Coefficient of variation (CV)3.3438237
Kurtosis30.806522
Mean1200.6875
Median Absolute Deviation (MAD)32
Skewness5.3381436
Sum96055
Variance16119320
MonotonicityNot monotonic
2023-12-12T23:39:22.286642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7
 
8.8%
4 5
 
6.2%
3 4
 
5.0%
9 3
 
3.8%
5 3
 
3.8%
2 2
 
2.5%
20 2
 
2.5%
7 2
 
2.5%
8 2
 
2.5%
184 1
 
1.2%
Other values (49) 49
61.3%
ValueCountFrequency (%)
1 7
8.8%
2 2
 
2.5%
3 4
5.0%
4 5
6.2%
5 3
3.8%
6 1
 
1.2%
7 2
 
2.5%
8 2
 
2.5%
9 3
3.8%
10 1
 
1.2%
ValueCountFrequency (%)
27664 1
1.2%
20961 1
1.2%
7675 1
1.2%
5562 1
1.2%
4494 1
1.2%
4125 1
1.2%
3819 1
1.2%
3619 1
1.2%
2836 1
1.2%
2772 1
1.2%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8172446 × 108
Minimum58910
Maximum8.9454726 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T23:39:22.446673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58910
5-th percentile869110
Q116119115
median1.0450016 × 108
Q32.5809602 × 108
95-th percentile6.2352403 × 108
Maximum8.9454726 × 108
Range8.9448835 × 108
Interquartile range (IQR)2.4197691 × 108

Descriptive statistics

Standard deviation2.0727997 × 108
Coefficient of variation (CV)1.1406278
Kurtosis1.3719833
Mean1.8172446 × 108
Median Absolute Deviation (MAD)1.0043762 × 108
Skewness1.3942876
Sum1.4537957 × 1010
Variance4.2964987 × 1016
MonotonicityNot monotonic
2023-12-12T23:39:22.593266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30901550 1
 
1.2%
80908570 1
 
1.2%
370777950 1
 
1.2%
229609500 1
 
1.2%
176422830 1
 
1.2%
254663110 1
 
1.2%
196894950 1
 
1.2%
327005210 1
 
1.2%
247974290 1
 
1.2%
240613380 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
58910 1
1.2%
111240 1
1.2%
728390 1
1.2%
837000 1
1.2%
870800 1
1.2%
1680310 1
1.2%
1877270 1
1.2%
2173670 1
1.2%
2333400 1
1.2%
2993390 1
1.2%
ValueCountFrequency (%)
894547260 1
1.2%
709602250 1
1.2%
703187500 1
1.2%
627837520 1
1.2%
623297000 1
1.2%
564441230 1
1.2%
558049500 1
1.2%
520595730 1
1.2%
507031750 1
1.2%
493255380 1
1.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6754.8375
Minimum1
Maximum127838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T23:39:22.756499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.85
Q157.5
median131
Q31515.75
95-th percentile34508.8
Maximum127838
Range127837
Interquartile range (IQR)1458.25

Descriptive statistics

Standard deviation21355.313
Coefficient of variation (CV)3.1614843
Kurtosis25.302351
Mean6754.8375
Median Absolute Deviation (MAD)126.5
Skewness4.8501249
Sum540387
Variance4.5604938 × 108
MonotonicityNot monotonic
2023-12-12T23:39:22.936398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
6 4
 
5.0%
6990 2
 
2.5%
1 2
 
2.5%
4498 2
 
2.5%
1578 2
 
2.5%
218 2
 
2.5%
1313 2
 
2.5%
369 2
 
2.5%
26 2
 
2.5%
1810 2
 
2.5%
Other values (31) 58
72.5%
ValueCountFrequency (%)
1 2
2.5%
2 1
 
1.2%
3 1
 
1.2%
6 4
5.0%
8 1
 
1.2%
12 1
 
1.2%
15 2
2.5%
23 2
2.5%
24 2
2.5%
26 2
2.5%
ValueCountFrequency (%)
127838 2
2.5%
34790 2
2.5%
34494 2
2.5%
27374 2
2.5%
13587 2
2.5%
8952 2
2.5%
6990 2
2.5%
4498 2
2.5%
1810 2
2.5%
1578 2
2.5%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8407534 × 108
Minimum74370
Maximum5.8310364 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T23:39:23.103845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74370
5-th percentile17661012
Q11.1597796 × 108
median5.0975936 × 108
Q31.2716008 × 109
95-th percentile2.7177994 × 109
Maximum5.8310364 × 109
Range5.8309621 × 109
Interquartile range (IQR)1.1556229 × 109

Descriptive statistics

Standard deviation1.146911 × 109
Coefficient of variation (CV)1.2973001
Kurtosis7.4866305
Mean8.8407534 × 108
Median Absolute Deviation (MAD)4.4536514 × 108
Skewness2.4711866
Sum7.0726028 × 1010
Variance1.3154049 × 1018
MonotonicityNot monotonic
2023-12-12T23:39:23.264944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
238963200 2
 
2.5%
2411596520 2
 
2.5%
2678453950 2
 
2.5%
894180790 2
 
2.5%
3465362420 2
 
2.5%
522965190 2
 
2.5%
1410419050 2
 
2.5%
991785040 2
 
2.5%
1268162280 2
 
2.5%
1491901370 2
 
2.5%
Other values (34) 60
75.0%
ValueCountFrequency (%)
74370 1
1.2%
111240 1
1.2%
5878390 2
2.5%
18281150 2
2.5%
23248910 2
2.5%
28292290 1
1.2%
39647270 2
2.5%
48707060 2
2.5%
64394220 2
2.5%
71891880 2
2.5%
ValueCountFrequency (%)
5831036450 2
2.5%
3465362420 2
2.5%
2678453950 2
2.5%
2411596520 2
2.5%
2403486350 2
2.5%
1557466930 2
2.5%
1491901370 2
2.5%
1463849000 2
2.5%
1410419050 2
2.5%
1281916520 2
2.5%

Interactions

2023-12-12T23:39:19.633350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.479860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.859139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.246896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.737263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.567421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.943190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.329188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.854432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.651043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.030981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.421005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.960911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:18.762487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.139529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:39:19.524979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:39:23.378183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명체납액구간체납건수체납금액누적체납건수누적체납금액
시군구명1.0000.9990.0000.0000.0000.0000.0000.000
자치단체코드0.9991.0000.0000.0000.0000.0000.0000.000
세목명0.0000.0001.0000.0000.3810.4390.4590.695
체납액구간0.0000.0000.0001.0000.0000.5220.2500.630
체납건수0.0000.0000.3810.0001.0000.6200.8080.549
체납금액0.0000.0000.4390.5220.6201.0000.4720.846
누적체납건수0.0000.0000.4590.2500.8080.4721.0000.655
누적체납금액0.0000.0000.6950.6300.5490.8460.6551.000
2023-12-12T23:39:23.517953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간자치단체코드시군구명세목명
체납액구간1.0000.0000.0000.000
자치단체코드0.0001.0000.9740.000
시군구명0.0000.9741.0000.000
세목명0.0000.0000.0001.000
2023-12-12T23:39:23.648243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액시군구명자치단체코드세목명체납액구간
체납건수1.0000.4820.9420.5320.0000.0000.2500.000
체납금액0.4821.0000.3390.9110.0000.0000.1670.246
누적체납건수0.9420.3391.0000.4740.0000.0000.3250.132
누적체납금액0.5320.9110.4741.0000.0000.0000.2960.353
시군구명0.0000.0000.0000.0001.0000.9740.0000.000
자치단체코드0.0000.0000.0000.0000.9741.0000.0000.000
세목명0.2500.1670.3250.2960.0000.0001.0000.000
체납액구간0.0000.2460.1320.3530.0000.0000.0001.000

Missing values

2023-12-12T23:39:20.096856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:39:20.575396image/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
0경기도안산시 상록구412712022등록면허세10만원 미만908309015506990238963200
1경기도안산시 단원구412732022등록면허세10만원 미만1414497801406990238963200
2경기도안산시 단원구412732022등록면허세10만원~30만원미만11112401111240
3경기도안산시 상록구412712022자동차세10만원 미만4494201566650344941557466930
4경기도안산시 단원구412732022자동차세10만원 미만3819172019490344941557466930
5경기도안산시 상록구412712022자동차세10만원~30만원미만4125709602250347905831036450
6경기도안산시 단원구412732022자동차세10만원~30만원미만3619627837520347905831036450
7경기도안산시 상록구412712022자동차세30만원~50만원미만226790652101495512962750
8경기도안산시 단원구412732022자동차세30만원~50만원미만207724988601495512962750
9경기도안산시 상록구412712022자동차세50만원~1백만원미만7374248012171891880
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
70경기도안산시 단원구412732022취득세1백만원~3백만원미만203631094094172624860
71경기도안산시 단원구412732022취득세1천만원~3천만원미만610290847012204536530
72경기도안산시 상록구412712022취득세30만원~50만원미만830428204718281150
73경기도안산시 단원구412732022취득세30만원~50만원미만416803104718281150
74경기도안산시 상록구412712022취득세3백만원~5백만원미만4180027601564394220
75경기도안산시 단원구412732022취득세3백만원~5백만원미만4163544201564394220
76경기도안산시 상록구412712022취득세50만원~1백만원미만529933906948707060
77경기도안산시 단원구412732022취득세50만원~1백만원미만323334006948707060
78경기도안산시 상록구412712022취득세5백만원~1천만원미만96102717024171627330
79경기도안산시 단원구412732022취득세5백만원~1천만원미만85684612024171627330