Overview

Dataset statistics

Number of variables12
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory106.2 B

Variable types

Categorical6
Numeric6

Dataset

Description2017년부터 2022년까지 지방세 미환급 현황의 세목별, 납세자유형별(개인, 법인), 당해미환급건수 및 금액, 누적 미환급건수 및 금액에 대한 정보
Author경상남도 통영시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078260

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
미환급유형 has constant value ""Constant
당해미환급건수(건) is highly overall correlated with 당해미환급금액(원) and 2 other fieldsHigh correlation
당해미환급금액(원) is highly overall correlated with 당해미환급건수(건) and 2 other fieldsHigh correlation
누적미환급건수(건) is highly overall correlated with 당해미환급건수(건) and 2 other fieldsHigh correlation
누적미환급금액(원) is highly overall correlated with 당해미환급건수(건) and 2 other fieldsHigh correlation
당해미환급금액(원) has unique valuesUnique
누적미환급금액(원) has unique valuesUnique
누적미환급금액증감 has 7 (17.1%) zerosZeros

Reproduction

Analysis started2024-04-20 18:38:14.561852
Analysis finished2024-04-20 18:38:19.010030
Duration4.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
경상남도
41 

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 41
100.0%

Length

2024-04-21T03:38:19.058576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:19.133982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 41
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
통영시
41 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
통영시 41
100.0%

Length

2024-04-21T03:38:19.211022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:19.284506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통영시 41
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
48220
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48220
2nd row48220
3rd row48220
4th row48220
5th row48220

Common Values

ValueCountFrequency (%)
48220 41
100.0%

Length

2024-04-21T03:38:19.360214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:19.434374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48220 41
100.0%

세목명
Categorical

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
자동차세
12 
지방소득세
11 
재산세
7 
등록면허세
6 
주민세
3 

Length

Max length5
Median length4
Mean length4.1219512
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자동차세 12
29.3%
지방소득세 11
26.8%
재산세 7
17.1%
등록면허세 6
14.6%
주민세 3
 
7.3%
취득세 2
 
4.9%

Length

2024-04-21T03:38:19.535735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:19.668274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자동차세 12
29.3%
지방소득세 11
26.8%
재산세 7
17.1%
등록면허세 6
14.6%
주민세 3
 
7.3%
취득세 2
 
4.9%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.7561
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:19.765158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6700372
Coefficient of variation (CV)0.00082685095
Kurtosis-1.2564993
Mean2019.7561
Median Absolute Deviation (MAD)1
Skewness-0.13415404
Sum82810
Variance2.7890244
MonotonicityIncreasing
2024-04-21T03:38:19.846232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 8
19.5%
2021 8
19.5%
2022 8
19.5%
2020 7
17.1%
2019 6
14.6%
2017 4
9.8%
ValueCountFrequency (%)
2017 4
9.8%
2018 8
19.5%
2019 6
14.6%
2020 7
17.1%
2021 8
19.5%
2022 8
19.5%
ValueCountFrequency (%)
2022 8
19.5%
2021 8
19.5%
2020 7
17.1%
2019 6
14.6%
2018 8
19.5%
2017 4
9.8%

미환급유형
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
신규
41 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 41
100.0%

Length

2024-04-21T03:38:19.936442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:20.020892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 41
100.0%

납세자유형
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
개인
25 
법인
16 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 25
61.0%
법인 16
39.0%

Length

2024-04-21T03:38:20.115428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T03:38:20.191259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 25
61.0%
법인 16
39.0%

당해미환급건수(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)53.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.292683
Minimum1
Maximum431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:20.288245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median7
Q348
95-th percentile335
Maximum431
Range430
Interquartile range (IQR)46

Descriptive statistics

Standard deviation107.98385
Coefficient of variation (CV)1.8524426
Kurtosis4.6019833
Mean58.292683
Median Absolute Deviation (MAD)6
Skewness2.2940553
Sum2390
Variance11660.512
MonotonicityNot monotonic
2024-04-21T03:38:20.391246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 9
22.0%
2 4
 
9.8%
80 3
 
7.3%
9 3
 
7.3%
6 2
 
4.9%
4 2
 
4.9%
3 2
 
4.9%
8 2
 
4.9%
5 1
 
2.4%
372 1
 
2.4%
Other values (12) 12
29.3%
ValueCountFrequency (%)
1 9
22.0%
2 4
9.8%
3 2
 
4.9%
4 2
 
4.9%
5 1
 
2.4%
6 2
 
4.9%
7 1
 
2.4%
8 2
 
4.9%
9 3
 
7.3%
16 1
 
2.4%
ValueCountFrequency (%)
431 1
 
2.4%
372 1
 
2.4%
335 1
 
2.4%
227 1
 
2.4%
220 1
 
2.4%
154 1
 
2.4%
138 1
 
2.4%
80 3
7.3%
48 1
 
2.4%
47 1
 
2.4%

당해미환급금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean564384.63
Minimum60
Maximum4063360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:20.490362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile320
Q117990
median56190
Q3756340
95-th percentile2839350
Maximum4063360
Range4063300
Interquartile range (IQR)738350

Descriptive statistics

Standard deviation993503.67
Coefficient of variation (CV)1.7603308
Kurtosis5.6500435
Mean564384.63
Median Absolute Deviation (MAD)55490
Skewness2.4089153
Sum23139770
Variance9.8704954 × 1011
MonotonicityNot monotonic
2024-04-21T03:38:20.628103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
759550 1
 
2.4%
980 1
 
2.4%
731750 1
 
2.4%
320 1
 
2.4%
33390 1
 
2.4%
2839350 1
 
2.4%
30190 1
 
2.4%
30270 1
 
2.4%
790 1
 
2.4%
1401070 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
60 1
2.4%
170 1
2.4%
320 1
2.4%
700 1
2.4%
790 1
2.4%
980 1
2.4%
3660 1
2.4%
11330 1
2.4%
12360 1
2.4%
16140 1
2.4%
ValueCountFrequency (%)
4063360 1
2.4%
3838860 1
2.4%
2839350 1
2.4%
1782940 1
2.4%
1689860 1
2.4%
1401070 1
2.4%
1110790 1
2.4%
860550 1
2.4%
826330 1
2.4%
759550 1
2.4%

누적미환급건수(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.7561
Minimum1
Maximum1369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:20.729105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median27
Q398
95-th percentile720
Maximum1369
Range1368
Interquartile range (IQR)93

Descriptive statistics

Standard deviation295.07684
Coefficient of variation (CV)1.9703828
Kurtosis7.7869654
Mean149.7561
Median Absolute Deviation (MAD)24
Skewness2.7441408
Sum6140
Variance87070.339
MonotonicityNot monotonic
2024-04-21T03:38:20.822952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 4
 
9.8%
5 3
 
7.3%
3 3
 
7.3%
4 2
 
4.9%
6 2
 
4.9%
163 1
 
2.4%
1369 1
 
2.4%
45 1
 
2.4%
27 1
 
2.4%
367 1
 
2.4%
Other values (22) 22
53.7%
ValueCountFrequency (%)
1 4
9.8%
3 3
7.3%
4 2
4.9%
5 3
7.3%
6 2
4.9%
7 1
 
2.4%
8 1
 
2.4%
10 1
 
2.4%
14 1
 
2.4%
18 1
 
2.4%
ValueCountFrequency (%)
1369 1
2.4%
977 1
2.4%
720 1
2.4%
649 1
2.4%
521 1
2.4%
367 1
2.4%
301 1
2.4%
215 1
2.4%
178 1
2.4%
163 1
2.4%

누적미환급금액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1382979.3
Minimum60
Maximum11042320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:20.933873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile20170
Q1100050
median318370
Q31394010
95-th percentile7289180
Maximum11042320
Range11042260
Interquartile range (IQR)1293960

Descriptive statistics

Standard deviation2414105.2
Coefficient of variation (CV)1.7455831
Kurtosis6.7407867
Mean1382979.3
Median Absolute Deviation (MAD)284960
Skewness2.5701167
Sum56702150
Variance5.827904 × 1012
MonotonicityNot monotonic
2024-04-21T03:38:21.049408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1592350 1
 
2.4%
314710 1
 
2.4%
2036360 1
 
2.4%
313730 1
 
2.4%
489140 1
 
2.4%
7545050 1
 
2.4%
339020 1
 
2.4%
65790 1
 
2.4%
20960 1
 
2.4%
3407440 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
60 1
2.4%
11330 1
2.4%
20170 1
2.4%
20960 1
2.4%
22000 1
2.4%
33410 1
2.4%
35520 1
2.4%
56190 1
2.4%
60430 1
2.4%
65790 1
2.4%
ValueCountFrequency (%)
11042320 1
2.4%
7545050 1
2.4%
7289180 1
2.4%
4787330 1
2.4%
4486080 1
2.4%
3407440 1
2.4%
2703140 1
2.4%
2254560 1
2.4%
2036360 1
2.4%
1592350 1
2.4%

누적미환급금액증감
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9295.0488
Minimum0
Maximum183847
Zeros7
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size501.0 B
2024-04-21T03:38:21.153088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median152
Q3809
95-th percentile44673
Maximum183847
Range183847
Interquartile range (IQR)799

Descriptive statistics

Standard deviation32775.547
Coefficient of variation (CV)3.5261296
Kurtosis21.735697
Mean9295.0488
Median Absolute Deviation (MAD)152
Skewness4.5123802
Sum381097
Variance1.0742365 × 109
MonotonicityNot monotonic
2024-04-21T03:38:21.255215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 7
 
17.1%
143 2
 
4.9%
110 1
 
2.4%
3571 1
 
2.4%
1365 1
 
2.4%
166 1
 
2.4%
1023 1
 
2.4%
117 1
 
2.4%
2553 1
 
2.4%
32013 1
 
2.4%
Other values (24) 24
58.5%
ValueCountFrequency (%)
0 7
17.1%
1 1
 
2.4%
3 1
 
2.4%
8 1
 
2.4%
10 1
 
2.4%
12 1
 
2.4%
79 1
 
2.4%
82 1
 
2.4%
84 1
 
2.4%
110 1
 
2.4%
ValueCountFrequency (%)
183847 1
2.4%
97941 1
2.4%
44673 1
2.4%
32013 1
2.4%
8599 1
2.4%
3571 1
2.4%
2553 1
2.4%
1365 1
2.4%
1135 1
2.4%
1023 1
2.4%

Interactions

2024-04-21T03:38:18.154097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:15.860771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.417983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.856864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.318331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.739449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.223698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:15.972607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.481178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.931310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.386662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.804135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.287858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.139011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.541671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.015282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.450439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.867190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.364692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.214114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.618797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.097672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.527375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.945247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.450176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.282679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.687183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.174364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.598544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.018487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.523832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.349504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:16.764589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.243500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:17.666503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:38:18.081179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T03:38:21.329700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도납세자유형당해미환급건수(건)당해미환급금액(원)누적미환급건수(건)누적미환급금액(원)누적미환급금액증감
세목명1.0000.0000.0000.0000.0000.0000.0000.000
과세년도0.0001.0000.0000.0000.3370.0000.0000.000
납세자유형0.0000.0001.0000.3480.3010.2760.3010.230
당해미환급건수(건)0.0000.0000.3481.0000.9870.9790.9890.000
당해미환급금액(원)0.0000.3370.3010.9871.0000.9060.9890.000
누적미환급건수(건)0.0000.0000.2760.9790.9061.0000.9270.000
누적미환급금액(원)0.0000.0000.3010.9890.9890.9271.0000.000
누적미환급금액증감0.0000.0000.2300.0000.0000.0000.0001.000
2024-04-21T03:38:21.421995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납세자유형세목명
납세자유형1.0000.000
세목명0.0001.000
2024-04-21T03:38:21.490864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도당해미환급건수(건)당해미환급금액(원)누적미환급건수(건)누적미환급금액(원)누적미환급금액증감세목명납세자유형
과세년도1.0000.1560.1330.1850.1930.0870.0000.000
당해미환급건수(건)0.1561.0000.8800.9200.782-0.1200.0000.343
당해미환급금액(원)0.1330.8801.0000.7790.772-0.3070.0000.295
누적미환급건수(건)0.1850.9200.7791.0000.8890.1850.0000.180
누적미환급금액(원)0.1930.7820.7720.8891.0000.2460.0000.295
누적미환급금액증감0.087-0.120-0.3070.1850.2461.0000.0000.266
세목명0.0000.0000.0000.0000.0000.0001.0000.000
납세자유형0.0000.3430.2950.1800.2950.2660.0001.000

Missing values

2024-04-21T03:38:18.781274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:38:18.943609image/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

시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수(건)당해미환급금액(원)누적미환급건수(건)누적미환급금액(원)누적미환급금액증감
0경상남도통영시48220자동차세2017신규개인807595501631592350110
1경상남도통영시48220자동차세2017신규법인74074026243530498
2경상남도통영시48220지방소득세2017신규개인263509905163767082
3경상남도통영시48220지방소득세2017신규법인11704312710183847
4경상남도통영시48220등록면허세2018신규개인490860510005010
5경상남도통영시48220자동차세2018신규개인13811107903012703140143
6경상남도통영시48220자동차세2018신규법인421460302649901135
7경상남도통영시48220재산세2018신규개인1601600
8경상남도통영시48220재산세2018신규법인3201703201700
9경상남도통영시48220주민세2018신규법인1561901561900
시도명시군구명자치단체코드세목명과세년도미환급유형납세자유형당해미환급건수(건)당해미환급금액(원)누적미환급건수(건)누적미환급금액(원)누적미환급금액증감
31경상남도통영시48220지방소득세2021신규법인2980831471032013
32경상남도통영시48220취득세2021신규개인1220001220000
33경상남도통영시48220등록면허세2022신규개인217990486604203571
34경상남도통영시48220자동차세2022신규개인4313838860136911042320188
35경상남도통영시48220자동차세2022신규법인1619479058521260168
36경상남도통영시48220재산세2022신규개인38826330658921208
37경상남도통영시48220주민세2022신규개인3334103334100
38경상남도통영시48220지방소득세2022신규개인3724063360720728918079
39경상남도통영시48220지방소득세2022신규법인63660143183708599
40경상남도통영시48220취득세2022신규개인6184730720673012