Overview

Dataset statistics

Number of variables10
Number of observations47
Missing cells4
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory88.8 B

Variable types

Categorical4
Numeric5
DateTime1

Dataset

Description지방세 비과세 감면율 현황으로 2017년도 취득세 37 재산세51 주민세 8 자동차세 1 2018년도 취득세 23 재산세50 주민세2 자동차세 1 2019년도 재산세51 주민세 2 취득세 21 자동차세 1
URLhttps://www.data.go.kr/data/15078944/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 2 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 부과금액 and 1 other fieldsHigh correlation
비과세금액 has 4 (8.5%) missing valuesMissing
비과세금액 has 7 (14.9%) zerosZeros
부과금액 has 4 (8.5%) zerosZeros
비과세감면율 has 10 (21.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:00:11.316069
Analysis finished2023-12-12 04:00:14.519513
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
전라남도
47 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 47
100.0%

Length

2023-12-12T13:00:14.589020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:00:14.690651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 47
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
화순군
47 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화순군 47
100.0%

Length

2023-12-12T13:00:14.800786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:00:14.917346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화순군 47
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
46790
47 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46790
2nd row46790
3rd row46790
4th row46790
5th row46790

Common Values

ValueCountFrequency (%)
46790 47
100.0%

Length

2023-12-12T13:00:15.015012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:00:15.105237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46790 47
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
교육세
6 
재산세
6 
주민세
6 
취득세
6 
자동차세
6 
Other values (3)
17 

Length

Max length7
Median length3
Mean length3.893617
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교육세 6
12.8%
재산세 6
12.8%
주민세 6
12.8%
취득세 6
12.8%
자동차세 6
12.8%
등록면허세 6
12.8%
지역자원시설세 6
12.8%
등록세 5
10.6%

Length

2023-12-12T13:00:15.240287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:00:15.400972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 6
12.8%
재산세 6
12.8%
주민세 6
12.8%
취득세 6
12.8%
자동차세 6
12.8%
등록면허세 6
12.8%
지역자원시설세 6
12.8%
등록세 5
10.6%

과세년도
Real number (ℝ)

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.4681
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T13:00:15.530783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7301805
Coefficient of variation (CV)0.0008567506
Kurtosis-1.2647144
Mean2019.4681
Median Absolute Deviation (MAD)1
Skewness0.043008724
Sum94915
Variance2.9935245
MonotonicityIncreasing
2023-12-12T13:00:15.647823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 8
17.0%
2018 8
17.0%
2019 8
17.0%
2020 8
17.0%
2022 8
17.0%
2021 7
14.9%
ValueCountFrequency (%)
2017 8
17.0%
2018 8
17.0%
2019 8
17.0%
2020 8
17.0%
2021 7
14.9%
2022 8
17.0%
ValueCountFrequency (%)
2022 8
17.0%
2021 7
14.9%
2020 8
17.0%
2019 8
17.0%
2018 8
17.0%
2017 8
17.0%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct37
Distinct (%)86.0%
Missing4
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean6.8172574 × 108
Minimum0
Maximum3.982338 × 109
Zeros7
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T13:00:15.783083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15510500
median1.02168 × 108
Q36.871555 × 108
95-th percentile3.2730007 × 109
Maximum3.982338 × 109
Range3.982338 × 109
Interquartile range (IQR)6.81645 × 108

Descriptive statistics

Standard deviation1.1727098 × 109
Coefficient of variation (CV)1.7202077
Kurtosis1.4120207
Mean6.8172574 × 108
Median Absolute Deviation (MAD)97518000
Skewness1.6784483
Sum2.9314207 × 1010
Variance1.3752484 × 1018
MonotonicityNot monotonic
2023-12-12T13:00:15.960625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 7
 
14.9%
107631000 1
 
2.1%
2288907000 1
 
2.1%
102168000 1
 
2.1%
13747000 1
 
2.1%
143015000 1
 
2.1%
3558279000 1
 
2.1%
6150000 1
 
2.1%
653995000 1
 
2.1%
107803000 1
 
2.1%
Other values (27) 27
57.4%
(Missing) 4
 
8.5%
ValueCountFrequency (%)
0 7
14.9%
2212000 1
 
2.1%
3326000 1
 
2.1%
4650000 1
 
2.1%
5071000 1
 
2.1%
5950000 1
 
2.1%
6100000 1
 
2.1%
6150000 1
 
2.1%
13747000 1
 
2.1%
21930000 1
 
2.1%
ValueCountFrequency (%)
3982338000 1
2.1%
3558279000 1
2.1%
3292086000 1
2.1%
3101233000 1
2.1%
2780963000 1
2.1%
2722514000 1
2.1%
2288907000 1
2.1%
1955978000 1
2.1%
1477120000 1
2.1%
1113910000 1
2.1%

감면금액
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1612753 × 108
Minimum4000
Maximum5.981523 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T13:00:16.156642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4000
5-th percentile6000
Q119643000
median98324000
Q35.656235 × 108
95-th percentile3.8389228 × 109
Maximum5.981523 × 109
Range5.981519 × 109
Interquartile range (IQR)5.459805 × 108

Descriptive statistics

Standard deviation1.3851065 × 109
Coefficient of variation (CV)1.9341618
Kurtosis5.7940255
Mean7.1612753 × 108
Median Absolute Deviation (MAD)98291000
Skewness2.4919244
Sum3.3657994 × 1010
Variance1.9185201 × 1018
MonotonicityNot monotonic
2023-12-12T13:00:16.765991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
6000 2
 
4.3%
4000 1
 
2.1%
317656000 1
 
2.1%
35655000 1
 
2.1%
5981523000 1
 
2.1%
320274000 1
 
2.1%
139734000 1
 
2.1%
35095000 1
 
2.1%
7000 1
 
2.1%
788688000 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
4000 1
2.1%
5000 1
2.1%
6000 2
4.3%
7000 1
2.1%
33000 1
2.1%
945000 1
2.1%
1276000 1
2.1%
2192000 1
2.1%
2758000 1
2.1%
3345000 1
2.1%
ValueCountFrequency (%)
5981523000 1
2.1%
5056585000 1
2.1%
4019779000 1
2.1%
3416925000 1
2.1%
2818996000 1
2.1%
2698378000 1
2.1%
1248184000 1
2.1%
1235518000 1
2.1%
1101683000 1
2.1%
1067859000 1
2.1%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.4330296 × 109
Minimum0
Maximum4.14179 × 1010
Zeros4
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T13:00:16.975958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.507109 × 109
median5.385873 × 109
Q31.368906 × 1010
95-th percentile3.3754311 × 1010
Maximum4.14179 × 1010
Range4.14179 × 1010
Interquartile range (IQR)1.2181951 × 1010

Descriptive statistics

Standard deviation1.1503122 × 1010
Coefficient of variation (CV)1.2194515
Kurtosis0.90475667
Mean9.4330296 × 109
Median Absolute Deviation (MAD)4.09235 × 109
Skewness1.411555
Sum4.4335239 × 1011
Variance1.3232181 × 1020
MonotonicityNot monotonic
2023-12-12T13:00:17.176304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 4
 
8.5%
31801809000 1
 
2.1%
8799306000 1
 
2.1%
2108050000 1
 
2.1%
24893197000 1
 
2.1%
28008358000 1
 
2.1%
2008609000 1
 
2.1%
1069821000 1
 
2.1%
7259491000 1
 
2.1%
9743125000 1
 
2.1%
Other values (34) 34
72.3%
ValueCountFrequency (%)
0 4
8.5%
50739000 1
 
2.1%
902812000 1
 
2.1%
966492000 1
 
2.1%
1002305000 1
 
2.1%
1069821000 1
 
2.1%
1293523000 1
 
2.1%
1330344000 1
 
2.1%
1406878000 1
 
2.1%
1607340000 1
 
2.1%
ValueCountFrequency (%)
41417900000 1
2.1%
38288194000 1
2.1%
34591098000 1
2.1%
31801809000 1
2.1%
29747629000 1
2.1%
28008358000 1
2.1%
24893197000 1
2.1%
23386592000 1
2.1%
19285992000 1
2.1%
18767883000 1
2.1%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.598085
Minimum0
Maximum51.78
Zeros10
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T13:00:17.345887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.06
median6.54
Q321.905
95-th percentile51.007
Maximum51.78
Range51.78
Interquartile range (IQR)20.845

Descriptive statistics

Standard deviation16.712682
Coefficient of variation (CV)1.2290468
Kurtosis0.38355401
Mean13.598085
Median Absolute Deviation (MAD)6.54
Skewness1.2607967
Sum639.11
Variance279.31375
MonotonicityNot monotonic
2023-12-12T13:00:17.516454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 10
 
21.3%
1.23 1
 
2.1%
29.96 1
 
2.1%
1.51 1
 
2.1%
7.64 1
 
2.1%
16.65 1
 
2.1%
44.62 1
 
2.1%
1.16 1
 
2.1%
17.96 1
 
2.1%
5.47 1
 
2.1%
Other values (28) 28
59.6%
ValueCountFrequency (%)
0.0 10
21.3%
0.98 1
 
2.1%
1.03 1
 
2.1%
1.09 1
 
2.1%
1.16 1
 
2.1%
1.23 1
 
2.1%
1.42 1
 
2.1%
1.51 1
 
2.1%
1.79 1
 
2.1%
2.3 1
 
2.1%
ValueCountFrequency (%)
51.78 1
2.1%
51.45 1
2.1%
51.25 1
2.1%
50.44 1
2.1%
47.48 1
2.1%
44.62 1
2.1%
37.67 1
2.1%
29.96 1
2.1%
24.8 1
2.1%
23.58 1
2.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
Minimum2023-06-14 00:00:00
Maximum2023-06-14 00:00:00
2023-12-12T13:00:17.652395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:17.771961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:00:13.741032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:11.587682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.066696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.654943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.128928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.856667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:11.677011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.182876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.745360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.245774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.971430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:11.777335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.306993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.838598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.424015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:14.067242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:11.869119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.463097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.934562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.546203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:14.156798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:11.964269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:12.556126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.036731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:00:13.639434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:00:17.868454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.5630.8110.8170.782
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.5630.0001.0000.9570.7080.851
감면금액0.8110.0000.9571.0000.7760.882
부과금액0.8170.0000.7080.7761.0000.811
비과세감면율0.7820.0000.8510.8820.8111.000
2023-12-12T13:00:17.987446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도비과세금액감면금액부과금액비과세감면율세목명
과세년도1.0000.030-0.0090.115-0.0430.000
비과세금액0.0301.0000.7670.3210.8590.293
감면금액-0.0090.7671.0000.6280.7600.397
부과금액0.1150.3210.6281.0000.1780.573
비과세감면율-0.0430.8590.7600.1781.0000.524
세목명0.0000.2930.3970.5730.5241.000

Missing values

2023-12-12T13:00:14.278219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:00:14.455432image/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
0전라남도화순군46790교육세20170400053858730000.02023-06-14
1전라남도화순군46790등록세2017<NA>219200000.02023-06-14
2전라남도화순군46790재산세201727225140001067859000732042900051.782023-06-14
3전라남도화순군46790주민세20171076310003426700017653750008.042023-06-14
4전라남도화순군46790취득세2017228890700040197790001674586900037.672023-06-14
5전라남도화순군46790자동차세201743089000331522000382881940000.982023-06-14
6전라남도화순군46790등록면허세20175071000146461000140687800010.772023-06-14
7전라남도화순군46790지역자원시설세20171249270008798700090281200023.582023-06-14
8전라남도화순군46790교육세20180600056499450000.02023-06-14
9전라남도화순군46790등록세2018<NA>127600000.02023-06-14
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일
37전라남도화순군46790등록면허세2021332600012771500023976320005.472023-06-14
38전라남도화순군46790지역자원시설세202114368100034466000129352300013.772023-06-14
39전라남도화순군46790교육세202203300064222540000.02023-06-14
40전라남도화순군46790등록세2022<NA>275800000.02023-06-14
41전라남도화순군46790재산세2022398233800010657950001063225100047.482023-06-14
42전라남도화순군46790주민세202261000002006000023969770001.092023-06-14
43전라남도화순군46790취득세2022195597800026983780001876788300024.82023-06-14
44전라남도화순군46790자동차세2022111056000307556000233865920001.792023-06-14
45전라남도화순군46790등록면허세202259500009914300016073400006.542023-06-14
46전라남도화순군46790지역자원시설세202215243200035489000133034400014.132023-06-14