Overview

Dataset statistics

Number of variables11
Number of observations32
Missing cells11
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory99.1 B

Variable types

Numeric5
Categorical5
DateTime1

Dataset

Description이 데이터는 2017~2020년 남원시 지방세 비과, 감면율 현황에 대하여 세목명, 비과세금액, 감면금액, 부과금액, 비과세감면율에 대한 데이터입니다.
URLhttps://www.data.go.kr/data/15079840/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 과세년도High correlation
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
과세년도 is highly overall correlated with 연번High correlation
비과세금액 has 8 (25.0%) missing valuesMissing
부과금액 has 3 (9.4%) missing valuesMissing
연번 has unique valuesUnique
감면금액 has unique valuesUnique
비과세감면율 has 7 (21.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:11:25.634509
Analysis finished2023-12-12 06:11:29.308936
Duration3.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:11:29.385121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2023-12-12T15:11:29.534708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
전라북도
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 32
100.0%

Length

2023-12-12T15:11:29.695085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:29.801672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 32
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
남원시
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남원시 32
100.0%

Length

2023-12-12T15:11:29.930561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:30.044944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남원시 32
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
45190
32 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45190
2nd row45190
3rd row45190
4th row45190
5th row45190

Common Values

ValueCountFrequency (%)
45190 32
100.0%

Length

2023-12-12T15:11:30.165033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:30.276141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45190 32
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
교육세
4 
등록세
4 
재산세
4 
주민세
4 
취득세
4 
Other values (3)
12 

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 4
12.5%
등록세 4
12.5%
재산세 4
12.5%
주민세 4
12.5%
취득세 4
12.5%
자동차세 4
12.5%
등록면허세 4
12.5%
지역자원시설세 4
12.5%

Length

2023-12-12T15:11:30.458931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:30.638180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 4
12.5%
등록세 4
12.5%
재산세 4
12.5%
주민세 4
12.5%
취득세 4
12.5%
자동차세 4
12.5%
등록면허세 4
12.5%
지역자원시설세 4
12.5%

과세년도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
2017
8 
2018
8 
2019
8 
2020
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
25.0%
2018 8
25.0%
2019 8
25.0%
2020 8
25.0%

Length

2023-12-12T15:11:30.822623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:30.940575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
25.0%
2018 8
25.0%
2019 8
25.0%
2020 8
25.0%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)100.0%
Missing8
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean9.0628054 × 108
Minimum7510000
Maximum4.499934 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:11:31.094304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7510000
5-th percentile8516150
Q136990500
median1.187735 × 108
Q38.767755 × 108
95-th percentile4.364522 × 109
Maximum4.499934 × 109
Range4.492424 × 109
Interquartile range (IQR)8.39785 × 108

Descriptive statistics

Standard deviation1.5379321 × 109
Coefficient of variation (CV)1.6969714
Kurtosis1.4409931
Mean9.0628054 × 108
Median Absolute Deviation (MAD)1.00987 × 108
Skewness1.7146609
Sum2.1750733 × 1010
Variance2.3652353 × 1018
MonotonicityNot monotonic
2023-12-12T15:11:31.253377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
47350000 1
 
3.1%
158657000 1
 
3.1%
9973000 1
 
3.1%
37062000 1
 
3.1%
1812186000 1
 
3.1%
9350000 1
 
3.1%
3319032000 1
 
3.1%
153846000 1
 
3.1%
25600000 1
 
3.1%
36776000 1
 
3.1%
Other values (14) 14
43.8%
(Missing) 8
25.0%
ValueCountFrequency (%)
7510000 1
3.1%
8369000 1
3.1%
9350000 1
3.1%
9973000 1
3.1%
25600000 1
3.1%
36776000 1
3.1%
37062000 1
3.1%
39576000 1
3.1%
39990000 1
3.1%
47350000 1
3.1%
ValueCountFrequency (%)
4499934000 1
3.1%
4381592000 1
3.1%
4267792000 1
3.1%
3319032000 1
3.1%
1812186000 1
3.1%
990858000 1
3.1%
838748000 1
3.1%
590339000 1
3.1%
158657000 1
3.1%
153846000 1
3.1%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9293391 × 108
Minimum5000
Maximum5.144688 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:11:31.407903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile7550
Q115137000
median1.478645 × 108
Q35.6517525 × 108
95-th percentile3.5016436 × 109
Maximum5.144688 × 109
Range5.144683 × 109
Interquartile range (IQR)5.5003825 × 108

Descriptive statistics

Standard deviation1.2750695 × 109
Coefficient of variation (CV)1.8401026
Kurtosis4.9276095
Mean6.9293391 × 108
Median Absolute Deviation (MAD)1.45428 × 108
Skewness2.3536897
Sum2.2173885 × 1010
Variance1.6258022 × 1018
MonotonicityNot monotonic
2023-12-12T15:11:31.582849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
5000 1
 
3.1%
7883000 1
 
3.1%
58133000 1
 
3.1%
189340000 1
 
3.1%
417253000 1
 
3.1%
3441515000 1
 
3.1%
18890000 1
 
3.1%
1061106000 1
 
3.1%
14186000 1
 
3.1%
30000 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
5000 1
3.1%
7000 1
3.1%
8000 1
3.1%
30000 1
3.1%
4843000 1
3.1%
6916000 1
3.1%
7883000 1
3.1%
14186000 1
3.1%
15454000 1
3.1%
16947000 1
3.1%
ValueCountFrequency (%)
5144688000 1
3.1%
3575134000 1
3.1%
3441515000 1
3.1%
3107635000 1
3.1%
1061106000 1
3.1%
1041720000 1
3.1%
1025989000 1
3.1%
958650000 1
3.1%
434017000 1
3.1%
417253000 1
3.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct29
Distinct (%)100.0%
Missing3
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean6.6407581 × 109
Minimum80103000
Maximum2.0465696 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:11:31.740908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80103000
5-th percentile1.0233442 × 109
Q11.300671 × 109
median6.280773 × 109
Q31.1254996 × 1010
95-th percentile1.832993 × 1010
Maximum2.0465696 × 1010
Range2.0385593 × 1010
Interquartile range (IQR)9.954325 × 109

Descriptive statistics

Standard deviation6.0879413 × 109
Coefficient of variation (CV)0.91675396
Kurtosis-0.25829876
Mean6.6407581 × 109
Median Absolute Deviation (MAD)4.980102 × 109
Skewness0.88578976
Sum1.9258198 × 1011
Variance3.7063029 × 1019
MonotonicityNot monotonic
2023-12-12T15:11:31.904194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
6763945000 1
 
3.1%
1228816000 1
 
3.1%
2097287000 1
 
3.1%
12016374000 1
 
3.1%
20465696000 1
 
3.1%
1447923000 1
 
3.1%
8031442000 1
 
3.1%
80103000 1
 
3.1%
6843413000 1
 
3.1%
1132029000 1
 
3.1%
Other values (19) 19
59.4%
(Missing) 3
 
9.4%
ValueCountFrequency (%)
80103000 1
3.1%
982697000 1
3.1%
1084315000 1
3.1%
1132029000 1
3.1%
1179715000 1
3.1%
1228816000 1
3.1%
1235958000 1
3.1%
1300671000 1
3.1%
1447923000 1
3.1%
1470067000 1
3.1%
ValueCountFrequency (%)
20465696000 1
3.1%
18945822000 1
3.1%
17406092000 1
3.1%
16397136000 1
3.1%
12048451000 1
3.1%
12016374000 1
3.1%
11876826000 1
3.1%
11254996000 1
3.1%
8031442000 1
3.1%
7548046000 1
3.1%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.790937
Minimum0
Maximum78.5
Zeros7
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:11:32.061507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.3225
median10.095
Q323.275
95-th percentile74.1235
Maximum78.5
Range78.5
Interquartile range (IQR)19.9525

Descriptive statistics

Standard deviation22.571561
Coefficient of variation (CV)1.2687112
Kurtosis2.2372811
Mean17.790937
Median Absolute Deviation (MAD)10.095
Skewness1.7246148
Sum569.31
Variance509.47538
MonotonicityNot monotonic
2023-12-12T15:11:32.213186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 7
21.9%
5.04 1
 
3.1%
17.64 1
 
3.1%
9.5 1
 
3.1%
3.78 1
 
3.1%
25.67 1
 
3.1%
1.95 1
 
3.1%
54.54 1
 
3.1%
17.71 1
 
3.1%
19.52 1
 
3.1%
Other values (16) 16
50.0%
ValueCountFrequency (%)
0.0 7
21.9%
1.95 1
 
3.1%
3.78 1
 
3.1%
3.91 1
 
3.1%
3.98 1
 
3.1%
4.29 1
 
3.1%
4.61 1
 
3.1%
4.66 1
 
3.1%
5.04 1
 
3.1%
9.5 1
 
3.1%
ValueCountFrequency (%)
78.5 1
3.1%
75.24 1
3.1%
73.21 1
3.1%
54.54 1
3.1%
32.38 1
3.1%
27.08 1
3.1%
25.67 1
3.1%
25.36 1
3.1%
22.58 1
3.1%
22.55 1
3.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2023-12-12T15:11:32.325969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:32.427307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:11:28.346599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:25.918523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.445069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.992961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.426426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:28.428986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.039341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.573267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.072014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.530257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:28.527669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.158543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.712201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.159262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.620544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:28.623743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.249160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.781794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.233494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.744759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:28.746992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.344272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:26.878154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.331484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:27.888150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:11:32.504447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번세목명과세년도비과세금액감면금액부과금액비과세감면율
연번1.0000.0000.9740.0000.0000.0000.000
세목명0.0001.0000.0000.8580.7540.8600.825
과세년도0.9740.0001.0000.0000.0000.0000.000
비과세금액0.0000.8580.0001.0000.9250.8900.889
감면금액0.0000.7540.0000.9251.0000.9150.868
부과금액0.0000.8600.0000.8900.9151.0000.592
비과세감면율0.0000.8250.0000.8890.8680.5921.000
2023-12-12T15:11:32.623257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-12T15:11:32.722841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번비과세금액감면금액부과금액비과세감면율세목명과세년도
연번1.000-0.1200.1520.0160.0930.0000.814
비과세금액-0.1201.0000.5700.3100.7990.4830.000
감면금액0.1520.5701.0000.7000.7490.5610.000
부과금액0.0160.3100.7001.0000.0800.6790.000
비과세감면율0.0930.7990.7490.0801.0000.6120.000
세목명0.0000.4830.5610.6790.6121.0000.000
과세년도0.8140.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T15:11:28.904791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:11:29.119152image/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.
2023-12-12T15:11:29.248561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일자
01전라북도남원시45190교육세2017<NA>500061837130000.02020-12-31
12전라북도남원시45190등록세2017<NA>6916000<NA>0.02020-12-31
23전라북도남원시45190재산세201742677920001041720000676394500078.52020-12-31
34전라북도남원시45190주민세2017395760001545400011797150004.662020-12-31
45전라북도남원시45190취득세201759033900031076350001639713600022.552020-12-31
56전라북도남원시45190자동차세201791958000391141000112549960004.292020-12-31
67전라북도남원시45190등록면허세20178369000199355000147006700014.132020-12-31
78전라북도남원시45190지역자원시설세201714061300012548200098269700027.082020-12-31
89전라북도남원시45190교육세2018<NA>800062807730000.02020-12-31
910전라북도남원시45190등록세2018<NA>4843000<NA>0.02020-12-31
연번시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일자
2223전라북도남원시45190등록면허세201925600000188432000198405000010.792020-12-31
2324전라북도남원시45190지역자원시설세201915384600067095000113202900019.522020-12-31
2425전라북도남원시45190교육세2020<NA>3000068434130000.02020-12-31
2526전라북도남원시45190등록세2020<NA>141860008010300017.712020-12-31
2627전라북도남원시45190재산세202033190320001061106000803144200054.542020-12-31
2728전라북도남원시45190주민세202093500001889000014479230001.952020-12-31
2829전라북도남원시45190취득세2020181218600034415150002046569600025.672020-12-31
2930전라북도남원시45190자동차세202037062000417253000120163740003.782020-12-31
3031전라북도남원시45190등록면허세2020997300018934000020972870009.52020-12-31
3132전라북도남원시45190지역자원시설세202015865700058133000122881600017.642020-12-31