Overview

Dataset statistics

Number of variables12
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 KiB
Average record size in memory104.1 B

Variable types

Numeric5
Categorical6
DateTime1

Dataset

Description지방세 체납 현황에 대한 데이터로 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/15079724/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 과세년도High 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
과세년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-17 09:10:25.474844
Analysis finished2024-04-17 09:10:27.844458
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.5
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-17T18:10:27.906527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.05
Q131.25
median61.5
Q391.75
95-th percentile115.95
Maximum122
Range121
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation35.362409
Coefficient of variation (CV)0.57499853
Kurtosis-1.2
Mean61.5
Median Absolute Deviation (MAD)30.5
Skewness0
Sum7503
Variance1250.5
MonotonicityStrictly increasing
2024-04-17T18:10:28.262503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
93 1
 
0.8%
91 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
경기도
122 

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 122
100.0%

Length

2024-04-17T18:10:28.399261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:10:28.478966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 122
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
남양주시
122 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남양주시 122
100.0%

Length

2024-04-17T18:10:28.558390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:10:28.632554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남양주시 122
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
41360
122 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41360
2nd row41360
3rd row41360
4th row41360
5th row41360

Common Values

ValueCountFrequency (%)
41360 122
100.0%

Length

2024-04-17T18:10:28.711699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:10:28.786757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41360 122
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2018
42 
2019
42 
2017
38 

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 (%)
2018 42
34.4%
2019 42
34.4%
2017 38
31.1%

Length

2024-04-17T18:10:28.863325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:10:28.948505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 42
34.4%
2019 42
34.4%
2017 38
31.1%

세목명
Categorical

Distinct7
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
지방소득세
32 
재산세
29 
취득세
29 
자동차세
12 
주민세
12 
Other values (2)
8 

Length

Max length7
Median length3
Mean length3.8032787
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 32
26.2%
재산세 29
23.8%
취득세 29
23.8%
자동차세 12
 
9.8%
주민세 12
 
9.8%
등록면허세 5
 
4.1%
지역자원시설세 3
 
2.5%

Length

2024-04-17T18:10:29.047504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T18:10:29.148139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 32
26.2%
재산세 29
23.8%
취득세 29
23.8%
자동차세 12
 
9.8%
주민세 12
 
9.8%
등록면허세 5
 
4.1%
지역자원시설세 3
 
2.5%

체납액구간
Categorical

Distinct11
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10만원 미만
21 
10만원-30만원미만
16 
30만원-50만원미만
15 
50만원-1백만원미만
14 
1백만원-3백만원미만
10 
Other values (6)
46 

Length

Max length11
Median length11
Mean length10.163934
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 21
17.2%
10만원-30만원미만 16
13.1%
30만원-50만원미만 15
12.3%
50만원-1백만원미만 14
11.5%
1백만원-3백만원미만 10
8.2%
1천만원-3천만원미만 10
8.2%
3백만원-5백만원미만 9
7.4%
5백만원-1천만원미만 8
 
6.6%
5천만원-1억원미만 8
 
6.6%
3천만원-5천만원미만 6
 
4.9%

Length

2024-04-17T18:10:29.258605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 21
14.7%
미만 21
14.7%
10만원-30만원미만 16
11.2%
30만원-50만원미만 15
10.5%
50만원-1백만원미만 14
9.8%
1백만원-3백만원미만 10
7.0%
1천만원-3천만원미만 10
7.0%
3백만원-5백만원미만 9
6.3%
5백만원-1천만원미만 8
 
5.6%
5천만원-1억원미만 8
 
5.6%
Other values (2) 11
7.7%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean641.22951
Minimum1
Maximum13563
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-17T18:10:29.368180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15.25
median23
Q3219.5
95-th percentile3177
Maximum13563
Range13562
Interquartile range (IQR)214.25

Descriptive statistics

Standard deviation1887.9576
Coefficient of variation (CV)2.9442774
Kurtosis24.446663
Mean641.22951
Median Absolute Deviation (MAD)22
Skewness4.6305472
Sum78230
Variance3564383.8
MonotonicityNot monotonic
2024-04-17T18:10:29.490068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 11
 
9.0%
1 11
 
9.0%
8 6
 
4.9%
4 4
 
3.3%
6 4
 
3.3%
11 4
 
3.3%
15 3
 
2.5%
3 3
 
2.5%
19 2
 
1.6%
14 2
 
1.6%
Other values (67) 72
59.0%
ValueCountFrequency (%)
1 11
9.0%
2 11
9.0%
3 3
 
2.5%
4 4
 
3.3%
5 2
 
1.6%
6 4
 
3.3%
8 6
4.9%
9 2
 
1.6%
10 2
 
1.6%
11 4
 
3.3%
ValueCountFrequency (%)
13563 1
0.8%
10147 1
0.8%
7760 1
0.8%
6469 1
0.8%
4372 1
0.8%
4187 1
0.8%
3181 1
0.8%
3101 1
0.8%
3043 1
0.8%
2553 1
0.8%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6638378 × 108
Minimum216350
Maximum1.37438 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-17T18:10:29.602915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum216350
5-th percentile929454.5
Q110163280
median60091680
Q31.9999601 × 108
95-th percentile6.0590789 × 108
Maximum1.37438 × 109
Range1.3741637 × 109
Interquartile range (IQR)1.8983273 × 108

Descriptive statistics

Standard deviation2.5544987 × 108
Coefficient of variation (CV)1.5353051
Kurtosis6.8665322
Mean1.6638378 × 108
Median Absolute Deviation (MAD)56900035
Skewness2.4935615
Sum2.0298821 × 1010
Variance6.5254636 × 1016
MonotonicityNot monotonic
2024-04-17T18:10:29.714693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7482350 1
 
0.8%
48790050 1
 
0.8%
82908250 1
 
0.8%
132158750 1
 
0.8%
209835100 1
 
0.8%
277164910 1
 
0.8%
164619130 1
 
0.8%
7884260 1
 
0.8%
124374540 1
 
0.8%
1125213520 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
216350 1
0.8%
247990 1
0.8%
260680 1
0.8%
685620 1
0.8%
758370 1
0.8%
763200 1
0.8%
927550 1
0.8%
965640 1
0.8%
1183630 1
0.8%
1347610 1
0.8%
ValueCountFrequency (%)
1374380050 1
0.8%
1126077440 1
0.8%
1125213520 1
0.8%
1054850850 1
0.8%
715079830 1
0.8%
656506160 1
0.8%
606832490 1
0.8%
588340540 1
0.8%
584671320 1
0.8%
580935190 1
0.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2708.0492
Minimum1
Maximum51413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-17T18:10:29.831308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q137.75
median136
Q3694
95-th percentile20116.95
Maximum51413
Range51412
Interquartile range (IQR)656.25

Descriptive statistics

Standard deviation7699.58
Coefficient of variation (CV)2.8432202
Kurtosis17.817361
Mean2708.0492
Median Absolute Deviation (MAD)128.5
Skewness3.9989633
Sum330382
Variance59283533
MonotonicityNot monotonic
2024-04-17T18:10:29.948415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 4
 
3.3%
4 3
 
2.5%
7 3
 
2.5%
214 2
 
1.6%
37 2
 
1.6%
14 2
 
1.6%
1 2
 
1.6%
60 2
 
1.6%
136 2
 
1.6%
16 2
 
1.6%
Other values (95) 98
80.3%
ValueCountFrequency (%)
1 2
1.6%
2 1
 
0.8%
4 3
2.5%
5 1
 
0.8%
6 4
3.3%
7 3
2.5%
8 1
 
0.8%
9 2
1.6%
11 1
 
0.8%
14 2
1.6%
ValueCountFrequency (%)
51413 1
0.8%
37850 1
0.8%
27703 1
0.8%
27483 1
0.8%
24644 1
0.8%
21014 1
0.8%
20272 1
0.8%
17171 1
0.8%
16827 1
0.8%
11913 1
0.8%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6480194 × 108
Minimum216350
Maximum4.6282445 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-17T18:10:30.060150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum216350
5-th percentile9594987.5
Q176746280
median2.7186515 × 108
Q37.360488 × 108
95-th percentile2.2533845 × 109
Maximum4.6282445 × 109
Range4.6280282 × 109
Interquartile range (IQR)6.5930252 × 108

Descriptive statistics

Standard deviation7.9334149 × 108
Coefficient of variation (CV)1.4046366
Kurtosis8.0113208
Mean5.6480194 × 108
Median Absolute Deviation (MAD)2.298106 × 108
Skewness2.6090033
Sum6.8905836 × 1010
Variance6.2939072 × 1017
MonotonicityNot monotonic
2024-04-17T18:10:30.182811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25092820 1
 
0.8%
380603960 1
 
0.8%
195504110 1
 
0.8%
837922800 1
 
0.8%
725215770 1
 
0.8%
830715180 1
 
0.8%
546594400 1
 
0.8%
91815220 1
 
0.8%
390804460 1
 
0.8%
4628244540 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
216350 1
0.8%
704150 1
0.8%
952140 1
0.8%
1715340 1
0.8%
7555930 1
0.8%
8241550 1
0.8%
9589160 1
0.8%
9705710 1
0.8%
10464080 1
0.8%
14189230 1
0.8%
ValueCountFrequency (%)
4628244540 1
0.8%
3565819340 1
0.8%
3503031020 1
0.8%
2787951190 1
0.8%
2510968490 1
0.8%
2266773550 1
0.8%
2253581680 1
0.8%
2249639050 1
0.8%
2015830170 1
0.8%
1701996070 1
0.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2021-08-31 00:00:00
Maximum2021-08-31 00:00:00
2024-04-17T18:10:30.270495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:30.347356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T18:10:27.261910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:25.802121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.154211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.516296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.900317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.335229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:25.870835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.231343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.588680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.965952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.406931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:25.944339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.304417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.668085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.042441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.481710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.020782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.379248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.746902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.116691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.553695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.089601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.448771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:26.815211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T18:10:27.184150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T18:10:30.414030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
연번1.0000.9540.6990.0000.0000.0000.0980.303
과세년도0.9541.0000.0000.0000.0000.0000.0000.325
세목명0.6990.0001.0000.0000.3890.2980.4230.359
체납액구간0.0000.0000.0001.0000.0000.4250.0000.295
체납건수0.0000.0000.3890.0001.0000.6100.9940.708
체납금액0.0000.0000.2980.4250.6101.0000.5210.972
누적체납건수0.0980.0000.4230.0000.9940.5211.0000.612
누적체납금액0.3030.3250.3590.2950.7080.9720.6121.000
2024-04-17T18:10:30.508635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.000
세목명0.0000.0001.000
2024-04-17T18:10:30.587278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
연번1.000-0.0960.105-0.1070.0800.9200.4450.000
체납건수-0.0961.0000.3820.9490.3160.0000.2180.000
체납금액0.1050.3821.0000.2150.9540.0000.1620.204
누적체납건수-0.1070.9490.2151.0000.2030.0000.2400.000
누적체납금액0.0800.3160.9540.2031.0000.1480.1980.132
과세년도0.9200.0000.0000.0000.1481.0000.0000.000
세목명0.4450.2180.1620.2400.1980.0001.0000.000
체납액구간0.0000.0000.2040.0000.1320.0000.0001.000

Missing values

2024-04-17T18:10:27.654869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T18:10:27.787944image/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

연번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
01경기도남양주시413602017등록면허세10만원 미만59774823502023250928202021-08-31
12경기도남양주시413602017등록면허세10만원-30만원미만221635022163502021-08-31
23경기도남양주시413602017자동차세10만원 미만2553113477510171717396598102021-08-31
34경기도남양주시413602017자동차세10만원-30만원미만31815361446501682727879511902021-08-31
45경기도남양주시413602017자동차세30만원-50만원미만99330463406002065058602021-08-31
56경기도남양주시413602017자동차세50만원-1백만원미만1810049030121793843102021-08-31
67경기도남양주시413602017재산세10만원 미만14606596991068812829088302021-08-31
78경기도남양주시413602017재산세10만원-30만원미만5559126067024763964132402021-08-31
89경기도남양주시413602017재산세1백만원-3백만원미만48821890902284026062202021-08-31
910경기도남양주시413602017재산세1천만원-3천만원미만229138660376411474002021-08-31
연번시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일자
112113경기도남양주시413602019취득세10만원 미만29134761025495891602021-08-31
113114경기도남양주시413602019취득세10만원-30만원미만295578240165315309902021-08-31
114115경기도남양주시413602019취득세1백만원-3백만원미만13223131001081863466502021-08-31
115116경기도남양주시413602019취득세1억원-3억원미만1223465020713877992702021-08-31
116117경기도남양주시413602019취득세1천만원-3천만원미만460259300111951410202021-08-31
117118경기도남양주시413602019취득세30만원-50만원미만11450287040149669502021-08-31
118119경기도남양주시413602019취득세3백만원-5백만원미만2727513018656292602021-08-31
119120경기도남양주시413602019취득세50만원-1백만원미만1612032330117842474902021-08-31
120121경기도남양주시413602019취득세5백만원-1천만원미만427139890201605952502021-08-31
121122경기도남양주시413602019취득세5천만원-1억원미만317884809074485914802021-08-31