Overview

Dataset statistics

Number of variables12
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory108.7 B

Variable types

Categorical7
Numeric5

Dataset

Description충청남도 논산시의 지방세 미환급 현황 및 연간 누적 현황에 대한 데이터로 당해미환급금액,누적미환급건수 및 금액 등의 정보를 제공한다.
Author충청남도 논산시
URLhttps://www.data.go.kr/data/15079116/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
당해미환급건수 is highly overall correlated with 당해미환급금액High correlation
당해미환급금액 is highly overall correlated with 당해미환급건수High correlation
누적미환급건수 is highly overall correlated with 누적미환급금액 and 2 other fieldsHigh correlation
누적미환급금액 is highly overall correlated with 누적미환급건수 and 3 other fieldsHigh correlation
누적미환급금액증감 is highly overall correlated with 누적미환급건수 and 2 other fieldsHigh correlation
과세년도 is highly overall correlated with 누적미환급금액High correlation
미환급유형 is highly overall correlated with 누적미환급금액증감High correlation
납세자유형 is highly overall correlated with 누적미환급건수 and 1 other fieldsHigh correlation
당해미환급금액 has unique valuesUnique
누적미환급금액증감 has 3 (13.0%) zerosZeros

Reproduction

Analysis started2023-12-12 14:35:09.742223
Analysis finished2023-12-12 14:35:13.086653
Duration3.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
충청남도
23 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 23
100.0%

Length

2023-12-12T23:35:13.141678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:13.225548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 23
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
논산시
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
논산시 23
100.0%

Length

2023-12-12T23:35:13.318538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:13.397075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논산시 23
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
44230
23 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44230
2nd row44230
3rd row44230
4th row44230
5th row44230

Common Values

ValueCountFrequency (%)
44230 23
100.0%

Length

2023-12-12T23:35:13.486214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:13.594105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44230 23
100.0%

세목명
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
자동차세
8 
지방소득세
8 
재산세
5 
주민세
1 
등록면허세
1 

Length

Max length5
Median length4
Mean length4.1304348
Min length3

Unique

Unique2 ?
Unique (%)8.7%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 8
34.8%
지방소득세 8
34.8%
재산세 5
21.7%
주민세 1
 
4.3%
등록면허세 1
 
4.3%

Length

2023-12-12T23:35:13.720021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:13.844779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 8
34.8%
지방소득세 8
34.8%
재산세 5
21.7%
주민세 1
 
4.3%
등록면허세 1
 
4.3%

과세년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2020
12 
2021
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 12
52.2%
2021 11
47.8%

Length

2023-12-12T23:35:13.994797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:14.101234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 12
52.2%
2021 11
47.8%

미환급유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
신규
14 
주소불명
5 
사망
2 
송달분 미수령
2 

Length

Max length7
Median length2
Mean length2.8695652
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사망
2nd row신규
3rd row주소불명
4th row신규
5th row신규

Common Values

ValueCountFrequency (%)
신규 14
60.9%
주소불명 5
 
21.7%
사망 2
 
8.7%
송달분 미수령 2
 
8.7%

Length

2023-12-12T23:35:14.226926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:14.343793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 14
56.0%
주소불명 5
 
20.0%
사망 2
 
8.0%
송달분 2
 
8.0%
미수령 2
 
8.0%

납세자유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
개인
17 
법인
6 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
개인 17
73.9%
법인 6
 
26.1%

Length

2023-12-12T23:35:14.448686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:35:14.552658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 17
73.9%
법인 6
 
26.1%

당해미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.652174
Minimum1
Maximum350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:35:14.641832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.5
median4
Q312.5
95-th percentile219.9
Maximum350
Range349
Interquartile range (IQR)11

Descriptive statistics

Standard deviation91.096157
Coefficient of variation (CV)2.1870685
Kurtosis6.0128691
Mean41.652174
Median Absolute Deviation (MAD)3
Skewness2.5636125
Sum958
Variance8298.5099
MonotonicityNot monotonic
2023-12-12T23:35:14.759352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 6
26.1%
11 2
 
8.7%
5 2
 
8.7%
4 2
 
8.7%
3 2
 
8.7%
2 2
 
8.7%
221 1
 
4.3%
8 1
 
4.3%
77 1
 
4.3%
350 1
 
4.3%
Other values (3) 3
13.0%
ValueCountFrequency (%)
1 6
26.1%
2 2
 
8.7%
3 2
 
8.7%
4 2
 
8.7%
5 2
 
8.7%
8 1
 
4.3%
11 2
 
8.7%
14 1
 
4.3%
22 1
 
4.3%
77 1
 
4.3%
ValueCountFrequency (%)
350 1
4.3%
221 1
4.3%
210 1
4.3%
77 1
4.3%
22 1
4.3%
14 1
4.3%
11 2
8.7%
8 1
4.3%
5 2
8.7%
4 2
8.7%

당해미환급금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean797771.74
Minimum910
Maximum6020220
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:35:14.872357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum910
5-th percentile3036
Q110850
median93540
Q3244350
95-th percentile3644498
Maximum6020220
Range6019310
Interquartile range (IQR)233500

Descriptive statistics

Standard deviation1655911.7
Coefficient of variation (CV)2.0756711
Kurtosis3.9256819
Mean797771.74
Median Absolute Deviation (MAD)86550
Skewness2.1906013
Sum18348750
Variance2.7420436 × 1012
MonotonicityNot monotonic
2023-12-12T23:35:15.290155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
106630 1
 
4.3%
3649950 1
 
4.3%
59140 1
 
4.3%
109010 1
 
4.3%
3595430 1
 
4.3%
910 1
 
4.3%
11000 1
 
4.3%
202730 1
 
4.3%
217270 1
 
4.3%
283660 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
910 1
4.3%
2650 1
4.3%
6510 1
4.3%
6990 1
4.3%
8470 1
4.3%
10700 1
4.3%
11000 1
4.3%
12600 1
4.3%
30220 1
4.3%
49190 1
4.3%
ValueCountFrequency (%)
6020220 1
4.3%
3649950 1
4.3%
3595430 1
4.3%
3489500 1
4.3%
283660 1
4.3%
271430 1
4.3%
217270 1
4.3%
202730 1
4.3%
111000 1
4.3%
109010 1
4.3%

누적미환급건수
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.86957
Minimum1
Maximum757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:35:15.420197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2
Q110.5
median169
Q3401
95-th percentile757
Maximum757
Range756
Interquartile range (IQR)390.5

Descriptive statistics

Standard deviation265.27932
Coefficient of variation (CV)1.1490441
Kurtosis-0.3073877
Mean230.86957
Median Absolute Deviation (MAD)166
Skewness0.93227011
Sum5310
Variance70373.119
MonotonicityNot monotonic
2023-12-12T23:35:15.570154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
418 3
13.0%
169 3
13.0%
757 3
13.0%
384 3
13.0%
15 2
8.7%
1 2
8.7%
3 2
8.7%
12 1
 
4.3%
4 1
 
4.3%
26 1
 
4.3%
Other values (2) 2
8.7%
ValueCountFrequency (%)
1 2
8.7%
3 2
8.7%
4 1
 
4.3%
9 1
 
4.3%
12 1
 
4.3%
15 2
8.7%
26 1
 
4.3%
37 1
 
4.3%
169 3
13.0%
384 3
13.0%
ValueCountFrequency (%)
757 3
13.0%
418 3
13.0%
384 3
13.0%
169 3
13.0%
37 1
 
4.3%
26 1
 
4.3%
15 2
8.7%
12 1
 
4.3%
9 1
 
4.3%
4 1
 
4.3%

누적미환급금액
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4609550.9
Minimum9740
Maximum12060730
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:35:15.710419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9740
5-th percentile10890
Q169800
median6086150
Q38422305
95-th percentile12060730
Maximum12060730
Range12050990
Interquartile range (IQR)8352505

Descriptive statistics

Standard deviation4792122.9
Coefficient of variation (CV)1.0396073
Kurtosis-1.5337647
Mean4609550.9
Median Absolute Deviation (MAD)5974580
Skewness0.3642909
Sum1.0601967 × 108
Variance2.2964442 × 1013
MonotonicityNot monotonic
2023-12-12T23:35:15.852145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
6086150 3
13.0%
6569630 3
13.0%
12060730 3
13.0%
10274980 3
13.0%
69800 2
8.7%
98370 1
 
4.3%
12600 1
 
4.3%
10700 1
 
4.3%
9740 1
 
4.3%
93540 1
 
4.3%
Other values (4) 4
17.4%
ValueCountFrequency (%)
9740 1
4.3%
10700 1
4.3%
12600 1
4.3%
23600 1
4.3%
68880 1
4.3%
69800 2
8.7%
93540 1
4.3%
98370 1
4.3%
272530 1
4.3%
315640 1
4.3%
ValueCountFrequency (%)
12060730 3
13.0%
10274980 3
13.0%
6569630 3
13.0%
6086150 3
13.0%
315640 1
 
4.3%
272530 1
 
4.3%
98370 1
 
4.3%
93540 1
 
4.3%
69800 2
8.7%
68880 1
 
4.3%

누적미환급금액증감
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74191.668
Minimum0
Maximum1129018.7
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:35:15.981910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q143.59
median114.55
Q34767.425
95-th percentile418908.31
Maximum1129018.7
Range1129018.7
Interquartile range (IQR)4723.835

Descriptive statistics

Standard deviation249008.22
Coefficient of variation (CV)3.3562829
Kurtosis16.115476
Mean74191.668
Median Absolute Deviation (MAD)114.55
Skewness3.9375028
Sum1706408.4
Variance6.2005095 × 1010
MonotonicityNot monotonic
2023-12-12T23:35:16.134811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 3
 
13.0%
5607.73 1
 
4.3%
100.34 1
 
4.3%
16.47 1
 
4.3%
9325.72 1
 
4.3%
185.78 1
 
4.3%
1129018.68 1
 
4.3%
114.55 1
 
4.3%
34.43 1
 
4.3%
45.28 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
0.0 3
13.0%
16.47 1
 
4.3%
34.43 1
 
4.3%
41.9 1
 
4.3%
45.28 1
 
4.3%
49.62 1
 
4.3%
66.75 1
 
4.3%
88.27 1
 
4.3%
100.34 1
 
4.3%
114.55 1
 
4.3%
ValueCountFrequency (%)
1129018.68 1
4.3%
455021.89 1
4.3%
93886.12 1
4.3%
9325.72 1
4.3%
5607.73 1
4.3%
5383.02 1
4.3%
4151.83 1
4.3%
2320.38 1
4.3%
724.09 1
4.3%
225.51 1
4.3%

Interactions

2023-12-12T23:35:12.222213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.166292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.667911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.163639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.699762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.325960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.286233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.786310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.280013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.804679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.426772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.382455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.884613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.401631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.906563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.529345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.478070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.984415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.504814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.009132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.651826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:10.580219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.078499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:11.606355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:35:12.116716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:35:16.237653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.4320.4860.000
과세년도0.0001.0000.3610.0000.0240.0000.5700.8820.082
미환급유형0.0000.3611.0000.4920.0000.0000.5310.6750.631
납세자유형0.0000.0000.4921.0000.0000.0000.7490.7050.000
당해미환급건수0.0000.0240.0000.0001.0001.0000.4360.4190.000
당해미환급금액0.0000.0000.0000.0001.0001.0000.6590.6670.000
누적미환급건수0.4320.5700.5310.7490.4360.6591.0000.9870.322
누적미환급금액0.4860.8820.6750.7050.4190.6670.9871.0000.442
누적미환급금액증감0.0000.0820.6310.0000.0000.0000.3220.4421.000
2023-12-12T23:35:16.397777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형미환급유형세목명과세년도
납세자유형1.0000.3080.0000.000
미환급유형0.3081.0000.0000.216
세목명0.0000.0001.0000.000
과세년도0.0000.2160.0001.000
2023-12-12T23:35:16.520993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감세목명과세년도미환급유형납세자유형
당해미환급건수1.0000.9000.4560.348-0.1420.0000.0000.0000.000
당해미환급금액0.9001.0000.4300.402-0.1630.0000.0000.0000.000
누적미환급건수0.4560.4301.0000.8920.6850.3440.3650.2160.510
누적미환급금액0.3480.4020.8921.0000.6890.3440.6380.3330.510
누적미환급금액증감-0.142-0.1630.6850.6891.0000.0000.1170.6320.000
세목명0.0000.0000.3440.3440.0001.0000.0000.0000.000
과세년도0.0000.0000.3650.6380.1170.0001.0000.2160.000
미환급유형0.0000.0000.2160.3330.6320.0000.2161.0000.308
납세자유형0.0000.0000.5100.5100.0000.0000.0000.3081.000

Missing values

2023-12-12T23:35:12.804755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:35:13.017707image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
0충청남도논산시44230자동차세2020사망개인1110663041860861505607.73
1충청남도논산시44230자동차세2020신규개인2213649950418608615066.75
2충청남도논산시44230자동차세2020주소불명개인811100041860861505383.02
3충청남도논산시44230자동차세2020신규법인5302201298370225.51
4충청남도논산시44230재산세2020신규개인449190156980041.9
5충청남도논산시44230재산세2020주소불명개인184701569800724.09
6충청남도논산시44230재산세2020신규법인1126001126000.0
7충청남도논산시44230주민세2020신규개인1107001107000.0
8충청남도논산시44230지방소득세2020사망개인16990169656963093886.12
9충청남도논산시44230지방소득세2020신규개인773489500169656963088.27
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수당해미환급금액누적미환급건수누적미환급금액누적미환급금액증감
13충청남도논산시44230자동차세2021송달분 미수령개인1265075712060730455021.89
14충청남도논산시44230자동차세2021신규개인350602022075712060730100.34
15충청남도논산시44230자동차세2021주소불명개인11283660757120607304151.83
16충청남도논산시44230자동차세2021신규법인142172702631564045.28
17충청남도논산시44230재산세2021신규개인222027303727253034.43
18충청남도논산시44230재산세2021신규법인211000323600114.55
19충청남도논산시44230지방소득세2021송달분 미수령개인1910384102749801129018.68
20충청남도논산시44230지방소득세2021신규개인210359543038410274980185.78
21충청남도논산시44230지방소득세2021주소불명개인4109010384102749809325.72
22충청남도논산시44230지방소득세2021신규법인55914096888016.47