Overview

Dataset statistics

Number of variables9
Number of observations58
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory80.3 B

Variable types

Categorical5
Numeric4

Dataset

Description대구광역시 중구의 연도별 지방세 과세 및 비과세 현황(건수, 금액 등)을 세목별로 제공합니다.- 시도명,시군구명,자치단체코드,과세년도,세목명,과세건수,과세금액,비과세건수,비과세금액
Author대구광역시 중구
URLhttps://www.data.go.kr/data/15079637/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세건수 is highly overall correlated with 과세금액 and 3 other fieldsHigh correlation
과세금액 is highly overall correlated with 과세건수 and 3 other fieldsHigh correlation
비과세건수 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
비과세금액 is highly overall correlated with 과세건수 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 과세건수 and 1 other fieldsHigh correlation
과세건수 has 16 (27.6%) zerosZeros
과세금액 has 16 (27.6%) zerosZeros
비과세건수 has 23 (39.7%) zerosZeros
비과세금액 has 23 (39.7%) zerosZeros

Reproduction

Analysis started2023-12-12 20:29:15.154876
Analysis finished2023-12-12 20:29:17.756879
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
대구광역시
58 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 58
100.0%

Length

2023-12-13T05:29:18.169488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:29:18.270808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 58
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
중구
58 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 58
100.0%

Length

2023-12-13T05:29:18.370673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:29:18.470513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 58
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
27110
58 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27110
2nd row27110
3rd row27110
4th row27110
5th row27110

Common Values

ValueCountFrequency (%)
27110 58
100.0%

Length

2023-12-13T05:29:18.585165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:29:18.703146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27110 58
100.0%

과세년도
Categorical

Distinct5
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size596.0 B
2018
12 
2019
12 
2020
12 
2021
12 
2017
10 

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 12
20.7%
2019 12
20.7%
2020 12
20.7%
2021 12
20.7%
2017 10
17.2%

Length

2023-12-13T05:29:18.825827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:29:18.967255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 12
20.7%
2019 12
20.7%
2020 12
20.7%
2021 12
20.7%
2017 10
17.2%

세목명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
취득세
5 
주민세
5 
재산세
5 
자동차세
5 
담배소비세
5 
Other values (7)
33 

Length

Max length7
Median length5
Mean length4.2586207
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취득세
2nd row주민세
3rd row재산세
4th row자동차세
5th row담배소비세

Common Values

ValueCountFrequency (%)
취득세 5
8.6%
주민세 5
8.6%
재산세 5
8.6%
자동차세 5
8.6%
담배소비세 5
8.6%
등록면허세 5
8.6%
도시계획세 5
8.6%
지역자원시설세 5
8.6%
지방소득세 5
8.6%
교육세 5
8.6%
Other values (2) 8
13.8%

Length

2023-12-13T05:29:19.120173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 5
8.6%
주민세 5
8.6%
재산세 5
8.6%
자동차세 5
8.6%
담배소비세 5
8.6%
등록면허세 5
8.6%
도시계획세 5
8.6%
지역자원시설세 5
8.6%
지방소득세 5
8.6%
교육세 5
8.6%
Other values (2) 8
13.8%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53507.707
Minimum0
Maximum256260
Zeros16
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size654.0 B
2023-12-13T05:29:19.268272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median41830.5
Q367877.5
95-th percentile247191.2
Maximum256260
Range256260
Interquartile range (IQR)67877.5

Descriptive statistics

Standard deviation67737.257
Coefficient of variation (CV)1.2659346
Kurtosis3.8191624
Mean53507.707
Median Absolute Deviation (MAD)32613.5
Skewness2.0393231
Sum3103447
Variance4.588336 × 109
MonotonicityNot monotonic
2023-12-13T05:29:19.424171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 16
27.6%
16297 1
 
1.7%
239186 1
 
1.7%
18104 1
 
1.7%
33362 1
 
1.7%
73831 1
 
1.7%
93525 1
 
1.7%
6 1
 
1.7%
42052 1
 
1.7%
61328 1
 
1.7%
Other values (33) 33
56.9%
ValueCountFrequency (%)
0 16
27.6%
6 1
 
1.7%
7 1
 
1.7%
15695 1
 
1.7%
16297 1
 
1.7%
16439 1
 
1.7%
17086 1
 
1.7%
18104 1
 
1.7%
33362 1
 
1.7%
37672 1
 
1.7%
ValueCountFrequency (%)
256260 1
1.7%
253236 1
1.7%
250785 1
1.7%
246557 1
1.7%
239186 1
1.7%
95990 1
1.7%
93525 1
1.7%
92415 1
1.7%
90924 1
1.7%
89616 1
1.7%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.01896 × 1010
Minimum0
Maximum1.20043 × 1011
Zeros16
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size654.0 B
2023-12-13T05:29:19.610583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.206757 × 109
Q32.6339135 × 1010
95-th percentile8.6377258 × 1010
Maximum1.20043 × 1011
Range1.20043 × 1011
Interquartile range (IQR)2.6339135 × 1010

Descriptive statistics

Standard deviation2.9081831 × 1010
Coefficient of variation (CV)1.4404362
Kurtosis3.4908491
Mean2.01896 × 1010
Median Absolute Deviation (MAD)5.206757 × 109
Skewness1.9682192
Sum1.1709968 × 1012
Variance8.4575288 × 1020
MonotonicityNot monotonic
2023-12-13T05:29:19.846984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 16
27.6%
73263680000 1
 
1.7%
17706862000 1
 
1.7%
114807000000 1
 
1.7%
4166529000 1
 
1.7%
36286737000 1
 
1.7%
17243233000 1
 
1.7%
5074000000 1
 
1.7%
4414686000 1
 
1.7%
5119563000 1
 
1.7%
Other values (33) 33
56.9%
ValueCountFrequency (%)
0 16
27.6%
4166529000 1
 
1.7%
4378848000 1
 
1.7%
4414686000 1
 
1.7%
4422498000 1
 
1.7%
4525411000 1
 
1.7%
4844502000 1
 
1.7%
4858553000 1
 
1.7%
4918773000 1
 
1.7%
4981593000 1
 
1.7%
ValueCountFrequency (%)
120043000000 1
1.7%
114807000000 1
1.7%
92935659000 1
1.7%
85219893000 1
1.7%
73263680000 1
1.7%
63768615000 1
1.7%
57085660000 1
1.7%
50005428000 1
1.7%
47112191000 1
1.7%
42419127000 1
1.7%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3437.2586
Minimum0
Maximum19733
Zeros23
Zeros (%)39.7%
Negative0
Negative (%)0.0%
Memory size654.0 B
2023-12-13T05:29:20.023923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median683.5
Q34672.5
95-th percentile17281.15
Maximum19733
Range19733
Interquartile range (IQR)4672.5

Descriptive statistics

Standard deviation5706.6258
Coefficient of variation (CV)1.6602259
Kurtosis2.115045
Mean3437.2586
Median Absolute Deviation (MAD)683.5
Skewness1.8056009
Sum199361
Variance32565577
MonotonicityNot monotonic
2023-12-13T05:29:20.191136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 23
39.7%
15 2
 
3.4%
1831 1
 
1.7%
887 1
 
1.7%
14 1
 
1.7%
1623 1
 
1.7%
16661 1
 
1.7%
19733 1
 
1.7%
7203 1
 
1.7%
1396 1
 
1.7%
Other values (25) 25
43.1%
ValueCountFrequency (%)
0 23
39.7%
14 1
 
1.7%
15 2
 
3.4%
17 1
 
1.7%
18 1
 
1.7%
610 1
 
1.7%
757 1
 
1.7%
887 1
 
1.7%
995 1
 
1.7%
1173 1
 
1.7%
ValueCountFrequency (%)
19733 1
1.7%
19450 1
1.7%
18421 1
1.7%
17080 1
1.7%
16661 1
1.7%
15360 1
1.7%
13158 1
1.7%
8306 1
1.7%
7997 1
1.7%
7363 1
1.7%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.070002 × 109
Minimum0
Maximum1.5056929 × 1010
Zeros23
Zeros (%)39.7%
Negative0
Negative (%)0.0%
Memory size654.0 B
2023-12-13T05:29:20.341320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median28750500
Q31.0456022 × 109
95-th percentile1.1820554 × 1010
Maximum1.5056929 × 1010
Range1.5056929 × 1010
Interquartile range (IQR)1.0456022 × 109

Descriptive statistics

Standard deviation4.1927829 × 109
Coefficient of variation (CV)2.025497
Kurtosis2.4612836
Mean2.070002 × 109
Median Absolute Deviation (MAD)28750500
Skewness1.9867704
Sum1.2006012 × 1011
Variance1.7579428 × 1019
MonotonicityNot monotonic
2023-12-13T05:29:20.482722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 23
39.7%
2000 3
 
5.2%
3000 2
 
3.4%
6459752000 1
 
1.7%
288222000 1
 
1.7%
6237438000 1
 
1.7%
2436039000 1
 
1.7%
12596948000 1
 
1.7%
340590000 1
 
1.7%
318199000 1
 
1.7%
Other values (23) 23
39.7%
ValueCountFrequency (%)
0 23
39.7%
2000 3
 
5.2%
3000 2
 
3.4%
25652000 1
 
1.7%
31849000 1
 
1.7%
35195000 1
 
1.7%
46883000 1
 
1.7%
280789000 1
 
1.7%
288222000 1
 
1.7%
290365000 1
 
1.7%
ValueCountFrequency (%)
15056929000 1
1.7%
13079720000 1
1.7%
12596948000 1
1.7%
11683543000 1
1.7%
11540570000 1
1.7%
11236678000 1
1.7%
11160164000 1
1.7%
8710470000 1
1.7%
6459752000 1
1.7%
6237438000 1
1.7%

Interactions

2023-12-13T05:29:16.945715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:15.485522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:15.945511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.433289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:17.064105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:15.597758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.062475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.556630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:17.191544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:15.718157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.172950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.680707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:17.322026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:15.827231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.316204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:29:16.816488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:29:20.607372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명과세건수과세금액비과세건수비과세금액
과세년도1.0000.0000.0000.0000.0000.000
세목명0.0001.0001.0000.8440.7370.702
과세건수0.0001.0001.0000.7410.6760.313
과세금액0.0000.8440.7411.0000.8280.846
비과세건수0.0000.7370.6760.8281.0000.823
비과세금액0.0000.7020.3130.8460.8231.000
2023-12-13T05:29:20.721363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-13T05:29:20.812018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세건수과세금액비과세건수비과세금액과세년도세목명
과세건수1.0000.6160.6240.5450.0000.932
과세금액0.6161.0000.5240.5890.0000.547
비과세건수0.6240.5241.0000.9600.0000.408
비과세금액0.5450.5890.9601.0000.0000.413
과세년도0.0000.0000.0000.0001.0000.000
세목명0.9320.5470.4080.4130.0001.000

Missing values

2023-12-13T05:29:17.499830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:29:17.687907image/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

시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
0대구광역시중구271102017취득세162977326368000018316459752000
1대구광역시중구271102017주민세48985491877300053121295186000
2대구광역시중구271102017재산세69905283227440001315811236678000
3대구광역시중구271102017자동차세90924182950060007286411946000
4대구광역시중구271102017담배소비세0000
5대구광역시중구271102017등록면허세37672437884800061046883000
6대구광역시중구271102017도시계획세0000
7대구광역시중구271102017지역자원시설세5423345254110001452298774000
8대구광역시중구271102017지방소득세392184241912700000
9대구광역시중구271102017교육세24655714140867000182000
시도명시군구명자치단체코드과세년도세목명과세건수과세금액비과세건수비과세금액
48대구광역시중구271102021재산세74211389177190001945013079720000
49대구광역시중구271102021자동차세95990193635980007363333356000
50대구광역시중구271102021레저세0000
51대구광역시중구271102021담배소비세0000
52대구광역시중구271102021지방소비세7485855300000
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