Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells2
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory83.7 B

Variable types

Categorical5
Numeric4

Dataset

Description충청남도 논산시의 지방세 금액 중 비과세·감면액이 차지하는 비율에대한 데이터로 기준연도,비과세금액,감면금액 등에 대한 정보를 제공한다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=351&beforeMenuCd=DOM_000000201001001000&publicdatapk=15079123

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 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 비과세금액 and 3 other fieldsHigh correlation
비과세금액 has 2 (8.7%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 3 (13.0%) zerosZeros
부과금액 has 2 (8.7%) zerosZeros
비과세감면율 has 5 (21.7%) zerosZeros

Reproduction

Analysis started2024-01-09 19:54:08.750506
Analysis finished2024-01-09 19:54:11.484307
Duration2.73 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

2024-01-10T04:54:11.572627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:54:11.694591image/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

2024-01-10T04:54:11.816149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:54:11.943928image/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

2024-01-10T04:54:12.062323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:54:12.190218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44230 23
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
교육세
3 
재산세
3 
주민세
3 
취득세
3 
자동차세
3 
Other values (3)
8 

Length

Max length7
Median length3
Mean length3.9130435
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 3
13.0%
재산세 3
13.0%
주민세 3
13.0%
취득세 3
13.0%
자동차세 3
13.0%
등록면허세 3
13.0%
지역자원시설세 3
13.0%
등록세 2
8.7%

Length

2024-01-10T04:54:12.327487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:54:12.433798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 3
13.0%
재산세 3
13.0%
주민세 3
13.0%
취득세 3
13.0%
자동차세 3
13.0%
등록면허세 3
13.0%
지역자원시설세 3
13.0%
등록세 2
8.7%

과세년도
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2017
8 
2018
8 
2019
7 

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
34.8%
2018 8
34.8%
2019 7
30.4%

Length

2024-01-10T04:54:12.533663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:54:12.613309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
34.8%
2018 8
34.8%
2019 7
30.4%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)90.5%
Missing2
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean1.1607955 × 109
Minimum0
Maximum6.259379 × 109
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-10T04:54:12.691051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115618000
median1.11948 × 108
Q31.064273 × 109
95-th percentile6.011292 × 109
Maximum6.259379 × 109
Range6.259379 × 109
Interquartile range (IQR)1.048655 × 109

Descriptive statistics

Standard deviation2.1213548 × 109
Coefficient of variation (CV)1.8275009
Kurtosis2.1548386
Mean1.1607955 × 109
Median Absolute Deviation (MAD)1.11948 × 108
Skewness1.8859788
Sum2.4376706 × 1010
Variance4.5001463 × 1018
MonotonicityNot monotonic
2024-01-10T04:54:12.782643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 3
 
13.0%
42360000 1
 
4.3%
1064273000 1
 
4.3%
237350000 1
 
4.3%
12027000 1
 
4.3%
76283000 1
 
4.3%
2015606000 1
 
4.3%
48380000 1
 
4.3%
6259379000 1
 
4.3%
226881000 1
 
4.3%
Other values (9) 9
39.1%
(Missing) 2
 
8.7%
ValueCountFrequency (%)
0 3
13.0%
9971000 1
 
4.3%
12027000 1
 
4.3%
15618000 1
 
4.3%
42010000 1
 
4.3%
42360000 1
 
4.3%
48380000 1
 
4.3%
76283000 1
 
4.3%
111948000 1
 
4.3%
125196000 1
 
4.3%
ValueCountFrequency (%)
6259379000 1
4.3%
6011292000 1
4.3%
5756463000 1
4.3%
2111711000 1
4.3%
2015606000 1
4.3%
1064273000 1
4.3%
237350000 1
4.3%
226881000 1
4.3%
209958000 1
4.3%
125196000 1
4.3%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.98534 × 108
Minimum5000
Maximum5.126729 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-10T04:54:12.876058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile6200
Q123310500
median2.12026 × 108
Q31.231513 × 109
95-th percentile4.7917063 × 109
Maximum5.126729 × 109
Range5.126724 × 109
Interquartile range (IQR)1.2082025 × 109

Descriptive statistics

Standard deviation1.6190173 × 109
Coefficient of variation (CV)1.6213943
Kurtosis2.2518985
Mean9.98534 × 108
Median Absolute Deviation (MAD)2.12018 × 108
Skewness1.8491698
Sum2.2966282 × 1010
Variance2.6212171 × 1018
MonotonicityNot monotonic
2024-01-10T04:54:12.974322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
5000 1
 
4.3%
1022000 1
 
4.3%
153555000 1
 
4.3%
170992000 1
 
4.3%
663301000 1
 
4.3%
5126729000 1
 
4.3%
25365000 1
 
4.3%
1799725000 1
 
4.3%
8000 1
 
4.3%
222579000 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
5000 1
4.3%
6000 1
4.3%
8000 1
4.3%
1022000 1
4.3%
2454000 1
4.3%
21836000 1
4.3%
24785000 1
4.3%
25365000 1
4.3%
152848000 1
4.3%
153555000 1
4.3%
ValueCountFrequency (%)
5126729000 1
4.3%
4831950000 1
4.3%
4429513000 1
4.3%
1830673000 1
4.3%
1817930000 1
4.3%
1799725000 1
4.3%
663301000 1
4.3%
633461000 1
4.3%
624453000 1
4.3%
222579000 1
4.3%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0729178 × 1010
Minimum0
Maximum3.4279897 × 1010
Zeros2
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-10T04:54:13.083209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.641673 × 108
Q12.582816 × 109
median1.0923776 × 1010
Q31.6432393 × 1010
95-th percentile3.0240816 × 1010
Maximum3.4279897 × 1010
Range3.4279897 × 1010
Interquartile range (IQR)1.3849577 × 1010

Descriptive statistics

Standard deviation1.0498979 × 1010
Coefficient of variation (CV)0.97854463
Kurtosis-0.1646606
Mean1.0729178 × 1010
Median Absolute Deviation (MAD)8.419961 × 109
Skewness0.95327672
Sum2.4677109 × 1011
Variance1.1022857 × 1020
MonotonicityNot monotonic
2024-01-10T04:54:13.200883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 2
 
8.7%
10953887000 1
 
4.3%
20848625000 1
 
4.3%
2047285000 1
 
4.3%
2855806000 1
 
4.3%
20152258000 1
 
4.3%
34279897000 1
 
4.3%
2958201000 1
 
4.3%
12712528000 1
 
4.3%
11343364000 1
 
4.3%
Other values (12) 12
52.2%
ValueCountFrequency (%)
0 2
8.7%
1641673000 1
4.3%
1900518000 1
4.3%
2047285000 1
4.3%
2503815000 1
4.3%
2661817000 1
4.3%
2713814000 1
4.3%
2806229000 1
4.3%
2855806000 1
4.3%
2958201000 1
4.3%
ValueCountFrequency (%)
34279897000 1
4.3%
30358391000 1
4.3%
29182640000 1
4.3%
20848625000 1
4.3%
20669240000 1
4.3%
20152258000 1
4.3%
12712528000 1
4.3%
11993400000 1
4.3%
11343364000 1
4.3%
11263928000 1
4.3%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.971739
Minimum0
Maximum67.24
Zeros5
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-10T04:54:13.312387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.395
median6
Q321.625
95-th percentile65.19
Maximum67.24
Range67.24
Interquartile range (IQR)19.23

Descriptive statistics

Standard deviation21.4179
Coefficient of variation (CV)1.3409873
Kurtosis1.784227
Mean15.971739
Median Absolute Deviation (MAD)6
Skewness1.6639909
Sum367.35
Variance458.72643
MonotonicityNot monotonic
2024-01-10T04:54:13.403575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 5
21.7%
67.24 1
 
4.3%
19.09 1
 
4.3%
6.41 1
 
4.3%
3.67 1
 
4.3%
20.84 1
 
4.3%
2.49 1
 
4.3%
63.39 1
 
4.3%
23.65 1
 
4.3%
6.0 1
 
4.3%
Other values (9) 9
39.1%
ValueCountFrequency (%)
0.0 5
21.7%
2.38 1
 
4.3%
2.41 1
 
4.3%
2.49 1
 
4.3%
3.6 1
 
4.3%
3.61 1
 
4.3%
3.67 1
 
4.3%
6.0 1
 
4.3%
6.41 1
 
4.3%
9.09 1
 
4.3%
ValueCountFrequency (%)
67.24 1
4.3%
65.39 1
4.3%
63.39 1
4.3%
26.26 1
4.3%
23.65 1
4.3%
22.41 1
4.3%
20.84 1
4.3%
19.42 1
4.3%
19.09 1
4.3%
9.09 1
4.3%

Interactions

2024-01-10T04:54:10.292161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:08.972686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.462162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.744831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:10.482011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.053325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.523758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.842912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:10.681879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.330952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.585044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.968840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:10.887554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.394500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:09.653311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T04:54:10.113764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T04:54:13.468998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.8220.8830.8280.772
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.8220.0001.0000.8500.7930.785
감면금액0.8830.0000.8501.0000.8580.868
부과금액0.8280.0000.7930.8581.0000.335
비과세감면율0.7720.0000.7850.8680.3351.000
2024-01-10T04:54:13.548918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-01-10T04:54:13.619359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.8500.3590.8520.6570.000
감면금액0.8501.0000.6240.8280.7260.000
부과금액0.3590.6241.0000.2470.6040.000
비과세감면율0.8520.8280.2471.0000.5550.000
세목명0.6570.7260.6040.5551.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2024-01-10T04:54:11.126669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T04:54:11.406182image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0충청남도논산시44230교육세201705000109538870000.0
1충청남도논산시44230등록세2017<NA>102200000.0
2충청남도논산시44230재산세2017575646300018179300001126392800067.24
3충청남도논산시44230주민세2017423600002183600026618170002.41
4충청남도논산시44230취득세2017106427300048319500003035839100019.42
5충청남도논산시44230자동차세2017111948000633461000206692400003.61
6충청남도논산시44230등록면허세20171561800021202600025038150009.09
7충청남도논산시44230지역자원시설세2017209958000221066000164167300026.26
8충청남도논산시44230교육세201806000109237760000.0
9충청남도논산시44230등록세2018<NA>245400000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
13충청남도논산시44230자동차세2018125196000624453000208486250003.6
14충청남도논산시44230등록면허세2018997100015284800027138140006.0
15충청남도논산시44230지역자원시설세2018226881000222579000190051800023.65
16충청남도논산시44230교육세201908000113433640000.0
17충청남도논산시44230재산세2019625937900017997250001271252800063.39
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