Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells3
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory91.3 B

Variable types

Categorical5
Numeric4
DateTime1

Dataset

Description과세년도 2017~2019에 대한 지방세 세목별(교육세, 등록세, 제산세, 주민세, 취득세, 자동차세, 등록면허세, 지역자원시설세) 비과세금액, 감면금액, 부과금액, 비과세감면율에 대한 자료
Author충청남도 공주시
URLhttps://www.data.go.kr/data/15080737/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
비과세금액 has 3 (12.5%) missing valuesMissing
비과세금액 has 3 (12.5%) zerosZeros
부과금액 has 3 (12.5%) zerosZeros
비과세감면율 has 6 (25.0%) zerosZeros

Reproduction

Analysis started2024-04-21 13:23:29.964563
Analysis finished2024-04-21 13:23:35.039064
Duration5.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
충청남도
24 

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 24
100.0%

Length

2024-04-21T22:23:35.231513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:23:35.515212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 24
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
공주시
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공주시 24
100.0%

Length

2024-04-21T22:23:36.018824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:23:36.297243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공주시 24
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
44150
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44150
2nd row44150
3rd row44150
4th row44150
5th row44150

Common Values

ValueCountFrequency (%)
44150 24
100.0%

Length

2024-04-21T22:23:36.592276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:23:36.871597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44150 24
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
교육세
3 
등록세
3 
재산세
3 
주민세
3 
취득세
3 
Other values (3)
9 

Length

Max length7
Median length3
Mean length3.875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교육세
2nd row등록세
3rd row재산세
4th row주민세
5th row취득세

Common Values

ValueCountFrequency (%)
교육세 3
12.5%
등록세 3
12.5%
재산세 3
12.5%
주민세 3
12.5%
취득세 3
12.5%
자동차세 3
12.5%
등록면허세 3
12.5%
지역자원시설세 3
12.5%

Length

2024-04-21T22:23:37.218476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:23:37.585376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 3
12.5%
등록세 3
12.5%
재산세 3
12.5%
주민세 3
12.5%
취득세 3
12.5%
자동차세 3
12.5%
등록면허세 3
12.5%
지역자원시설세 3
12.5%

과세년도
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size320.0 B
2017
8 
2018
8 
2019
8 

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 (%)
2017 8
33.3%
2018 8
33.3%
2019 8
33.3%

Length

2024-04-21T22:23:37.988626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:23:38.290553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
33.3%
2018 8
33.3%
2019 8
33.3%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)90.5%
Missing3
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean2.177184 × 109
Minimum0
Maximum9.897685 × 109
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-04-21T22:23:38.613209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126975000
median3.23831 × 108
Q32.553342 × 109
95-th percentile9.553121 × 109
Maximum9.897685 × 109
Range9.897685 × 109
Interquartile range (IQR)2.526367 × 109

Descriptive statistics

Standard deviation3.3919771 × 109
Coefficient of variation (CV)1.5579653
Kurtosis1.0570477
Mean2.177184 × 109
Median Absolute Deviation (MAD)3.23831 × 108
Skewness1.5655251
Sum4.5720865 × 1010
Variance1.1505509 × 1019
MonotonicityNot monotonic
2024-04-21T22:23:39.006469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 3
 
12.5%
680828000 1
 
4.2%
3931801000 1
 
4.2%
358671000 1
 
4.2%
26975000 1
 
4.2%
88245000 1
 
4.2%
2553342000 1
 
4.2%
1587322000 1
 
4.2%
9897685000 1
 
4.2%
323831000 1
 
4.2%
Other values (9) 9
37.5%
(Missing) 3
 
12.5%
ValueCountFrequency (%)
0 3
12.5%
16362000 1
 
4.2%
19533000 1
 
4.2%
26975000 1
 
4.2%
84040000 1
 
4.2%
88245000 1
 
4.2%
94295000 1
 
4.2%
293787000 1
 
4.2%
323831000 1
 
4.2%
358671000 1
 
4.2%
ValueCountFrequency (%)
9897685000 1
4.2%
9553121000 1
4.2%
8878965000 1
4.2%
5834483000 1
4.2%
3931801000 1
4.2%
2553342000 1
4.2%
1587322000 1
4.2%
1497579000 1
4.2%
680828000 1
4.2%
358671000 1
4.2%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2086073 × 109
Minimum3000
Maximum7.313298 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-04-21T22:23:39.366377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile3150
Q193660750
median1.65101 × 108
Q38.4801625 × 108
95-th percentile6.7844941 × 109
Maximum7.313298 × 109
Range7.313295 × 109
Interquartile range (IQR)7.543555 × 108

Descriptive statistics

Standard deviation2.2516091 × 109
Coefficient of variation (CV)1.8629783
Kurtosis3.4424684
Mean1.2086073 × 109
Median Absolute Deviation (MAD)1.63344 × 108
Skewness2.1711003
Sum2.9006575 × 1010
Variance5.0697436 × 1018
MonotonicityNot monotonic
2024-04-21T22:23:39.766605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3000 2
 
8.3%
3510000 1
 
4.2%
117305000 1
 
4.2%
165723000 1
 
4.2%
534192000 1
 
4.2%
6343985000 1
 
4.2%
151981000 1
 
4.2%
1842608000 1
 
4.2%
14189000 1
 
4.2%
4000 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
3000 2
8.3%
4000 1
4.2%
3510000 1
4.2%
14189000 1
4.2%
22728000 1
4.2%
117305000 1
4.2%
134517000 1
4.2%
135355000 1
4.2%
150068000 1
4.2%
151981000 1
4.2%
ValueCountFrequency (%)
7313298000 1
4.2%
6862231000 1
4.2%
6343985000 1
4.2%
1876159000 1
4.2%
1842608000 1
4.2%
1670509000 1
4.2%
573852000 1
4.2%
540283000 1
4.2%
534192000 1
4.2%
223870000 1
4.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1443279 × 1010
Minimum0
Maximum4.0965732 × 1010
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-04-21T22:23:40.152550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.6424152 × 109
median7.2113625 × 109
Q31.6200475 × 1010
95-th percentile3.8843235 × 1010
Maximum4.0965732 × 1010
Range4.0965732 × 1010
Interquartile range (IQR)1.355806 × 1010

Descriptive statistics

Standard deviation1.2228431 × 1010
Coefficient of variation (CV)1.0686126
Kurtosis0.9546871
Mean1.1443279 × 1010
Median Absolute Deviation (MAD)6.294575 × 109
Skewness1.279053
Sum2.7463869 × 1011
Variance1.4953453 × 1020
MonotonicityNot monotonic
2024-04-21T22:23:40.521638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 3
 
12.5%
11647899000 1
 
4.2%
19723811000 1
 
4.2%
2091835000 1
 
4.2%
3051542000 1
 
4.2%
20393521000 1
 
4.2%
32596802000 1
 
4.2%
3252212000 1
 
4.2%
16063630000 1
 
4.2%
11170513000 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
0 3
12.5%
1833575000 1
 
4.2%
1863273000 1
 
4.2%
2091835000 1
 
4.2%
2825942000 1
 
4.2%
2979097000 1
 
4.2%
3033419000 1
 
4.2%
3051542000 1
 
4.2%
3109073000 1
 
4.2%
3252212000 1
 
4.2%
ValueCountFrequency (%)
40965732000 1
4.2%
39945547000 1
4.2%
32596802000 1
4.2%
20393521000 1
4.2%
19723811000 1
4.2%
16611009000 1
4.2%
16063630000 1
4.2%
15135226000 1
4.2%
14475407000 1
4.2%
11869625000 1
4.2%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.803333
Minimum0
Maximum75.51
Zeros6
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-04-21T22:23:40.862051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.2875
median15.405
Q329.585
95-th percentile73.0585
Maximum75.51
Range75.51
Interquartile range (IQR)27.2975

Descriptive statistics

Standard deviation25.512775
Coefficient of variation (CV)1.1188178
Kurtosis-0.15689326
Mean22.803333
Median Absolute Deviation (MAD)14.425
Skewness1.0181587
Sum547.28
Variance650.90168
MonotonicityNot monotonic
2024-04-21T22:23:41.233518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 6
25.0%
72.88 1
 
4.2%
22.75 1
 
4.2%
6.31 1
 
4.2%
3.05 1
 
4.2%
27.3 1
 
4.2%
53.48 1
 
4.2%
73.09 1
 
4.2%
25.43 1
 
4.2%
5.92 1
 
4.2%
Other values (9) 9
37.5%
ValueCountFrequency (%)
0.0 6
25.0%
3.05 1
 
4.2%
3.22 1
 
4.2%
3.96 1
 
4.2%
5.92 1
 
4.2%
6.31 1
 
4.2%
8.06 1
 
4.2%
22.75 1
 
4.2%
23.4 1
 
4.2%
25.43 1
 
4.2%
ValueCountFrequency (%)
75.51 1
4.2%
73.09 1
4.2%
72.88 1
4.2%
54.83 1
4.2%
53.48 1
4.2%
31.79 1
4.2%
28.85 1
4.2%
27.45 1
4.2%
27.3 1
4.2%
25.43 1
4.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
Minimum2019-12-31 00:00:00
Maximum2019-12-31 00:00:00
2024-04-21T22:23:41.572121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:41.864424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T22:23:33.294601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:30.328366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:31.330645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:32.326253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:33.541863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:30.567735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:31.578621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:32.578604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:33.797086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:30.818449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:31.832485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:32.825338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:34.036562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:31.078443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:32.071455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:23:33.050755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T22:23:42.076486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.8510.9530.9360.840
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.8510.0001.0001.0000.8340.851
감면금액0.9530.0001.0001.0001.0000.802
부과금액0.9360.0000.8341.0001.0000.857
비과세감면율0.8400.0000.8510.8020.8571.000
2024-04-21T22:23:42.343453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-04-21T22:23:42.588035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.6730.3090.9220.4410.000
감면금액0.6731.0000.7100.6750.6450.000
부과금액0.3090.7101.0000.3040.7960.000
비과세감면율0.9220.6750.3041.0000.6250.000
세목명0.4410.6450.7960.6251.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2024-04-21T22:23:34.390676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T22:23:34.859818image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일
0충청남도공주시44150교육세201703000116478990000.02019-12-31
1충청남도공주시44150등록세2017<NA>351000000.02019-12-31
2충청남도공주시44150재산세2017887896500016705090001447540700072.882019-12-31
3충청남도공주시44150주민세2017680828000134517000282594200028.852019-12-31
4충청남도공주시44150취득세2017393180100073132980004096573200027.452019-12-31
5충청남도공주시44150자동차세201784040000573852000166110090003.962019-12-31
6충청남도공주시44150등록면허세20171636200022387000029790970008.062019-12-31
7충청남도공주시44150지역자원시설세2017293787000135355000183357500023.42019-12-31
8충청남도공주시44150교육세201803000118696250000.02019-12-31
9충청남도공주시44150등록세2018<NA>2272800000.02019-12-31
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