Overview

Dataset statistics

Number of variables10
Number of observations125
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.6 KiB
Average record size in memory87.1 B

Variable types

Categorical6
Numeric4

Dataset

Description체납액 규모별 체납 건수를 납세자 유형별로 제공(시도명,시군구명,자치단체코드,과세년도,세목명,체납액구간,체납건수,체납금액,누적체납건수,누적체납금액)
URLhttps://www.data.go.kr/data/15079183/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 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:30:29.305092
Analysis finished2023-12-12 23:30:31.346690
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
경기도
125 

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 125
100.0%

Length

2023-12-13T08:30:31.407583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:30:31.499443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 125
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
고양시일산동구
45 
고양시덕양구
43 
고양시일산서구
37 

Length

Max length7
Median length7
Mean length6.656
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고양시덕양구
2nd row고양시일산동구
3rd row고양시일산서구
4th row고양시일산동구
5th row고양시덕양구

Common Values

ValueCountFrequency (%)
고양시일산동구 45
36.0%
고양시덕양구 43
34.4%
고양시일산서구 37
29.6%

Length

2023-12-13T08:30:31.602799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:30:31.723197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시일산동구 45
36.0%
고양시덕양구 43
34.4%
고양시일산서구 37
29.6%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
41285
45 
41281
43 
41287
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41281
2nd row41285
3rd row41287
4th row41285
5th row41281

Common Values

ValueCountFrequency (%)
41285 45
36.0%
41281 43
34.4%
41287 37
29.6%

Length

2023-12-13T08:30:31.838412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:30:31.953202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41285 45
36.0%
41281 43
34.4%
41287 37
29.6%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2022
125 

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 125
100.0%

Length

2023-12-13T08:30:32.083839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:30:32.179726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 125
100.0%

세목명
Categorical

Distinct7
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
지방소득세
35 
취득세
28 
재산세
27 
주민세
16 
자동차세
12 
Other values (2)
7 

Length

Max length7
Median length3
Mean length3.816
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 35
28.0%
취득세 28
22.4%
재산세 27
21.6%
주민세 16
12.8%
자동차세 12
 
9.6%
등록면허세 4
 
3.2%
지역자원시설세 3
 
2.4%

Length

2023-12-13T08:30:32.285388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:30:32.409198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 35
28.0%
취득세 28
22.4%
재산세 27
21.6%
주민세 16
12.8%
자동차세 12
 
9.6%
등록면허세 4
 
3.2%
지역자원시설세 3
 
2.4%

체납액구간
Categorical

Distinct13
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10만원 미만
21 
30만원~50만원미만
16 
50만원~1백만원미만
15 
10만원~30만원미만
14 
1백만원~3백만원미만
12 
Other values (8)
47 

Length

Max length11
Median length11
Mean length10.168
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 21
16.8%
30만원~50만원미만 16
12.8%
50만원~1백만원미만 15
12.0%
10만원~30만원미만 14
11.2%
1백만원~3백만원미만 12
9.6%
5백만원~1천만원미만 10
8.0%
3백만원~5백만원미만 9
7.2%
1천만원~3천만원미만 8
 
6.4%
5천만원~1억원미만 7
 
5.6%
3천만원~5천만원미만 5
 
4.0%
Other values (3) 8
 
6.4%

Length

2023-12-13T08:30:32.558313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 21
14.4%
미만 21
14.4%
30만원~50만원미만 16
11.0%
50만원~1백만원미만 15
10.3%
10만원~30만원미만 14
9.6%
1백만원~3백만원미만 12
8.2%
5백만원~1천만원미만 10
6.8%
3백만원~5백만원미만 9
6.2%
1천만원~3천만원미만 8
 
5.5%
5천만원~1억원미만 7
 
4.8%
Other values (4) 13
8.9%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean829.392
Minimum1
Maximum16837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T08:30:32.687498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median15
Q3275
95-th percentile3828.2
Maximum16837
Range16836
Interquartile range (IQR)271

Descriptive statistics

Standard deviation2373.6095
Coefficient of variation (CV)2.8618669
Kurtosis27.503393
Mean829.392
Median Absolute Deviation (MAD)14
Skewness4.8877897
Sum103674
Variance5634022.1
MonotonicityNot monotonic
2023-12-13T08:30:32.839042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 18
 
14.4%
3 6
 
4.8%
5 5
 
4.0%
9 5
 
4.0%
2 5
 
4.0%
11 4
 
3.2%
6 4
 
3.2%
4 4
 
3.2%
13 3
 
2.4%
10 2
 
1.6%
Other values (66) 69
55.2%
ValueCountFrequency (%)
1 18
14.4%
2 5
 
4.0%
3 6
 
4.8%
4 4
 
3.2%
5 5
 
4.0%
6 4
 
3.2%
7 1
 
0.8%
8 2
 
1.6%
9 5
 
4.0%
10 2
 
1.6%
ValueCountFrequency (%)
16837 1
0.8%
15182 1
0.8%
9244 1
0.8%
6455 1
0.8%
4155 1
0.8%
3995 1
0.8%
3857 1
0.8%
3713 1
0.8%
3147 1
0.8%
3088 1
0.8%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9581565 × 108
Minimum177430
Maximum1.1058197 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T08:30:33.300112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum177430
5-th percentile499196
Q19800050
median1.114724 × 108
Q32.9767104 × 108
95-th percentile6.4027834 × 108
Maximum1.1058197 × 109
Range1.1056422 × 109
Interquartile range (IQR)2.8787099 × 108

Descriptive statistics

Standard deviation2.321429 × 108
Coefficient of variation (CV)1.1855176
Kurtosis2.6076303
Mean1.9581565 × 108
Median Absolute Deviation (MAD)1.0839496 × 108
Skewness1.6171015
Sum2.4476956 × 1010
Variance5.3890325 × 1016
MonotonicityNot monotonic
2023-12-13T08:30:33.472075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47472300 1
 
0.8%
482518330 1
 
0.8%
836400390 1
 
0.8%
680160830 1
 
0.8%
588034010 1
 
0.8%
632627760 1
 
0.8%
304166770 1
 
0.8%
552583830 1
 
0.8%
398502530 1
 
0.8%
125185100 1
 
0.8%
Other values (115) 115
92.0%
ValueCountFrequency (%)
177430 1
0.8%
204860 1
0.8%
204970 1
0.8%
258180 1
0.8%
460050 1
0.8%
463500 1
0.8%
495930 1
0.8%
512260 1
0.8%
526800 1
0.8%
551240 1
0.8%
ValueCountFrequency (%)
1105819660 1
0.8%
1026368380 1
0.8%
870382520 1
0.8%
836400390 1
0.8%
680160830 1
0.8%
670702250 1
0.8%
642190980 1
0.8%
632627760 1
0.8%
625570760 1
0.8%
610277400 1
0.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7371.56
Minimum1
Maximum112365
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T08:30:33.632052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q148
median176
Q32323
95-th percentile39583
Maximum112365
Range112364
Interquartile range (IQR)2275

Descriptive statistics

Standard deviation19767.992
Coefficient of variation (CV)2.6816566
Kurtosis17.778871
Mean7371.56
Median Absolute Deviation (MAD)171
Skewness4.008033
Sum921445
Variance3.9077353 × 108
MonotonicityNot monotonic
2023-12-13T08:30:33.754576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
2 4
 
3.2%
212 3
 
2.4%
5642 3
 
2.4%
2112 3
 
2.4%
230 3
 
2.4%
1680 3
 
2.4%
453 3
 
2.4%
1 3
 
2.4%
48 3
 
2.4%
2348 3
 
2.4%
Other values (34) 94
75.2%
ValueCountFrequency (%)
1 3
2.4%
2 4
3.2%
3 2
1.6%
4 2
1.6%
5 1
 
0.8%
7 2
1.6%
9 2
1.6%
12 2
1.6%
17 3
2.4%
29 3
2.4%
ValueCountFrequency (%)
112365 3
2.4%
45249 3
2.4%
39583 3
2.4%
35666 3
2.4%
17820 3
2.4%
17785 3
2.4%
14164 3
2.4%
5642 3
2.4%
3521 3
2.4%
2348 3
2.4%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct49
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1676181 × 109
Minimum1223640
Maximum7.6667094 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T08:30:33.878748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1223640
5-th percentile7534430
Q11.5092148 × 108
median6.7223013 × 108
Q31.6588821 × 109
95-th percentile3.582326 × 109
Maximum7.6667094 × 109
Range7.6654858 × 109
Interquartile range (IQR)1.5079607 × 109

Descriptive statistics

Standard deviation1.4300915 × 109
Coefficient of variation (CV)1.2247939
Kurtosis8.4972959
Mean1.1676181 × 109
Median Absolute Deviation (MAD)6.3181658 × 108
Skewness2.5231964
Sum1.4595226 × 1011
Variance2.0451616 × 1018
MonotonicityNot monotonic
2023-12-13T08:30:34.039496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
502463820 3
 
2.4%
205714020 3
 
2.4%
150921480 3
 
2.4%
78345600 3
 
2.4%
511574290 3
 
2.4%
1031118550 3
 
2.4%
3582326010 3
 
2.4%
138124260 3
 
2.4%
3770697820 3
 
2.4%
672230130 3
 
2.4%
Other values (39) 95
76.0%
ValueCountFrequency (%)
1223640 1
 
0.8%
2388650 3
2.4%
6738050 3
2.4%
10719950 1
 
0.8%
11186860 3
2.4%
30218540 2
1.6%
40413550 3
2.4%
78345600 3
2.4%
104928950 3
2.4%
113338410 1
 
0.8%
ValueCountFrequency (%)
7666709390 3
2.4%
3770697820 3
2.4%
3582326010 3
2.4%
3092708890 3
2.4%
2567361070 3
2.4%
2343471410 3
2.4%
2262446940 3
2.4%
1819023490 3
2.4%
1780514810 3
2.4%
1748119980 3
2.4%

Interactions

2023-12-13T08:30:30.704732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:29.613421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:29.982746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.317495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.803519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:29.704735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.074418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.435278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.895829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:29.799192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.146914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.525751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:31.004126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:29.885458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.222957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:30:30.599460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:30:34.160058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명체납액구간체납건수체납금액누적체납건수누적체납금액
시군구명1.0001.0000.0000.0000.1560.2780.0000.000
자치단체코드1.0001.0000.0000.0000.1560.2780.0000.000
세목명0.0000.0001.0000.0000.3240.3800.5570.595
체납액구간0.0000.0000.0001.0000.1770.6040.5670.588
체납건수0.1560.1560.3240.1771.0000.4750.8010.740
체납금액0.2780.2780.3800.6040.4751.0000.3970.706
누적체납건수0.0000.0000.5570.5670.8010.3971.0000.756
누적체납금액0.0000.0000.5950.5880.7400.7060.7561.000
2023-12-13T08:30:34.298999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명자치단체코드시군구명
체납액구간1.0000.0000.0000.000
세목명0.0001.0000.0000.000
자치단체코드0.0000.0001.0001.000
시군구명0.0000.0001.0001.000
2023-12-13T08:30:34.425404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액시군구명자치단체코드세목명체납액구간
체납건수1.0000.4160.9110.6130.0620.0620.1970.081
체납금액0.4161.0000.2170.8830.1210.1210.2110.307
누적체납건수0.9110.2171.0000.5150.0000.0000.3970.338
누적체납금액0.6130.8830.5151.0000.0000.0000.4060.331
시군구명0.0620.1210.0000.0001.0001.0000.0000.000
자치단체코드0.0620.1210.0000.0001.0001.0000.0000.000
세목명0.1970.2110.3970.4060.0000.0001.0000.000
체납액구간0.0810.3070.3380.3310.0000.0000.0001.000

Missing values

2023-12-13T08:30:31.147129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:30:31.289608image/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
0경기도고양시덕양구412812022등록면허세10만원 미만13724747230014164502463820
1경기도고양시일산동구412852022등록면허세10만원 미만21457765230014164502463820
2경기도고양시일산서구412872022등록면허세10만원 미만10263608072014164502463820
3경기도고양시일산동구412852022등록면허세30만원~50만원미만146350031223640
4경기도고양시덕양구412812022자동차세10만원 미만3995179630120395831780514810
5경기도고양시일산동구412852022자동차세10만원 미만2913132491040395831780514810
6경기도고양시일산서구412872022자동차세10만원 미만189784932500395831780514810
7경기도고양시덕양구412812022자동차세10만원~30만원미만3713642190980452497666709390
8경기도고양시일산동구412852022자동차세10만원~30만원미만3088544033010452497666709390
9경기도고양시일산서구412872022자동차세10만원~30만원미만2125367055640452497666709390
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
115경기도고양시덕양구412812022취득세3천만원~5천만원미만31133384103113338410
116경기도고양시덕양구412812022취득세50만원~1백만원미만190401011278345600
117경기도고양시일산동구412852022취득세50만원~1백만원미만5361907011278345600
118경기도고양시일산서구412872022취득세50만원~1백만원미만152680011278345600
119경기도고양시덕양구412812022취득세5백만원~1천만원미만31893841017124529030
120경기도고양시일산동구412852022취득세5백만원~1천만원미만1980005017124529030
121경기도고양시일산서구412872022취득세5백만원~1천만원미만1839094017124529030
122경기도고양시덕양구412812022취득세5억원~10억원미만16102774001610277400
123경기도고양시일산동구412852022취득세5천만원~1억원미만1661847704278248720
124경기도고양시일산서구412872022취득세5천만원~1억원미만1691607404278248720