Overview

Dataset statistics

Number of variables10
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory87.6 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 체납액 규모별 체납 건수를 납세자 유형별로 제공하는 데이터 이며, 체납정책 수립시 참고를 위한 기초자료로 활용됩니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15078998&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납건수 and 1 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납금액 and 1 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-01-28 16:36:13.027022
Analysis finished2024-01-28 16:36:15.500060
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
인천광역시
84 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 84
100.0%

Length

2024-01-29T01:36:15.570256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T01:36:15.689752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 84
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
연수구
84 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연수구 84
100.0%

Length

2024-01-29T01:36:15.835021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T01:36:15.952781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연수구 84
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
28185
84 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28185
2nd row28185
3rd row28185
4th row28185
5th row28185

Common Values

ValueCountFrequency (%)
28185 84
100.0%

Length

2024-01-29T01:36:16.075045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T01:36:16.201025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28185 84
100.0%

과세년도
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
2021
43 
2020
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2021 43
51.2%
2020 41
48.8%

Length

2024-01-29T01:36:16.335150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T01:36:16.459141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 43
51.2%
2020 41
48.8%

세목명
Categorical

Distinct7
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size804.0 B
지방소득세
22 
재산세
21 
취득세
14 
주민세
12 
자동차세
8 
Other values (2)
7 

Length

Max length7
Median length3
Mean length3.8333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row등록면허세
2nd row등록면허세
3rd row자동차세
4th row자동차세
5th row자동차세

Common Values

ValueCountFrequency (%)
지방소득세 22
26.2%
재산세 21
25.0%
취득세 14
16.7%
주민세 12
14.3%
자동차세 8
 
9.5%
등록면허세 5
 
6.0%
지역자원시설세 2
 
2.4%

Length

2024-01-29T01:36:16.603000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T01:36:16.774568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 22
26.2%
재산세 21
25.0%
취득세 14
16.7%
주민세 12
14.3%
자동차세 8
 
9.5%
등록면허세 5
 
6.0%
지역자원시설세 2
 
2.4%

체납액구간
Categorical

Distinct11
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
10만원 미만
14 
10만원~30만원미만
12 
30만원~50만원미만
11 
50만원~1백만원미만
10 
1백만원~3백만원미만
8 
Other values (6)
29 

Length

Max length11
Median length11
Mean length10.190476
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10만원 미만
2nd row10만원~30만원미만
3rd row10만원 미만
4th row10만원~30만원미만
5th row30만원~50만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 14
16.7%
10만원~30만원미만 12
14.3%
30만원~50만원미만 11
13.1%
50만원~1백만원미만 10
11.9%
1백만원~3백만원미만 8
9.5%
1천만원~3천만원미만 6
7.1%
3백만원~5백만원미만 6
7.1%
5백만원~1천만원미만 5
 
6.0%
1억원~3억원미만 4
 
4.8%
3천만원~5천만원미만 4
 
4.8%

Length

2024-01-29T01:36:16.956937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 14
14.3%
미만 14
14.3%
10만원~30만원미만 12
12.2%
30만원~50만원미만 11
11.2%
50만원~1백만원미만 10
10.2%
1백만원~3백만원미만 8
8.2%
1천만원~3천만원미만 6
6.1%
3백만원~5백만원미만 6
6.1%
5백만원~1천만원미만 5
 
5.1%
1억원~3억원미만 4
 
4.1%
Other values (2) 8
8.2%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean581.95238
Minimum1
Maximum11367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-29T01:36:17.126127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median14.5
Q3215.25
95-th percentile3090
Maximum11367
Range11366
Interquartile range (IQR)211.25

Descriptive statistics

Standard deviation1530.1665
Coefficient of variation (CV)2.6293672
Kurtosis29.730492
Mean581.95238
Median Absolute Deviation (MAD)13.5
Skewness4.774701
Sum48884
Variance2341409.5
MonotonicityNot monotonic
2024-01-29T01:36:17.286467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 13
 
15.5%
2 4
 
4.8%
4 4
 
4.8%
9 3
 
3.6%
7 3
 
3.6%
3 3
 
3.6%
21 2
 
2.4%
15 2
 
2.4%
14 2
 
2.4%
13 2
 
2.4%
Other values (41) 46
54.8%
ValueCountFrequency (%)
1 13
15.5%
2 4
 
4.8%
3 3
 
3.6%
4 4
 
4.8%
5 2
 
2.4%
6 1
 
1.2%
7 3
 
3.6%
8 2
 
2.4%
9 3
 
3.6%
10 1
 
1.2%
ValueCountFrequency (%)
11367 1
1.2%
3649 1
1.2%
3562 1
1.2%
3151 1
1.2%
3132 1
1.2%
2852 1
1.2%
2837 1
1.2%
2725 1
1.2%
2593 1
1.2%
2497 1
1.2%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1739009 × 108
Minimum95040
Maximum6.3526738 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-29T01:36:17.447957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95040
5-th percentile405523.5
Q18705990
median67556760
Q31.6577641 × 108
95-th percentile4.4401798 × 108
Maximum6.3526738 × 108
Range6.3517234 × 108
Interquartile range (IQR)1.5707042 × 108

Descriptive statistics

Standard deviation1.4272675 × 108
Coefficient of variation (CV)1.215833
Kurtosis2.1697746
Mean1.1739009 × 108
Median Absolute Deviation (MAD)63580185
Skewness1.5876685
Sum9.8607676 × 109
Variance2.0370924 × 1016
MonotonicityNot monotonic
2024-01-29T01:36:17.620390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39459260 1
 
1.2%
37628350 1
 
1.2%
10079950 1
 
1.2%
10179370 1
 
1.2%
16827900 1
 
1.2%
252071690 1
 
1.2%
54018630 1
 
1.2%
96345140 1
 
1.2%
203746930 1
 
1.2%
39882560 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
95040 1
1.2%
102760 1
1.2%
109960 1
1.2%
287750 1
1.2%
402660 1
1.2%
421750 1
1.2%
494490 1
1.2%
787110 1
1.2%
1174010 1
1.2%
1587200 1
1.2%
ValueCountFrequency (%)
635267380 1
1.2%
511455750 1
1.2%
493547130 1
1.2%
465456060 1
1.2%
448026880 1
1.2%
421300860 1
1.2%
368172090 1
1.2%
364780700 1
1.2%
310242210 1
1.2%
297516610 1
1.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1371.0714
Minimum1
Maximum15859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-29T01:36:17.785497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16.5
median41
Q3353.5
95-th percentile10816.35
Maximum15859
Range15858
Interquartile range (IQR)347

Descriptive statistics

Standard deviation3510.3538
Coefficient of variation (CV)2.5602997
Kurtosis8.8238675
Mean1371.0714
Median Absolute Deviation (MAD)37.5
Skewness3.0848986
Sum115170
Variance12322584
MonotonicityNot monotonic
2024-01-29T01:36:17.965592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
7.1%
4 6
 
7.1%
3 4
 
4.8%
12 4
 
4.8%
2 3
 
3.6%
43 3
 
3.6%
55 2
 
2.4%
5 2
 
2.4%
44 2
 
2.4%
19 2
 
2.4%
Other values (49) 50
59.5%
ValueCountFrequency (%)
1 6
7.1%
2 3
3.6%
3 4
4.8%
4 6
7.1%
5 2
 
2.4%
7 1
 
1.2%
8 1
 
1.2%
9 1
 
1.2%
10 1
 
1.2%
11 1
 
1.2%
ValueCountFrequency (%)
15859 1
1.2%
14492 1
1.2%
14433 1
1.2%
13830 1
1.2%
11481 1
1.2%
7050 1
1.2%
7017 1
1.2%
4998 1
1.2%
4728 1
1.2%
3273 1
1.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0237171 × 108
Minimum95040
Maximum2.6542661 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-01-29T01:36:18.146092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95040
5-th percentile437980
Q116111135
median1.219143 × 108
Q33.5825487 × 108
95-th percentile1.367705 × 109
Maximum2.6542661 × 109
Range2.6541711 × 109
Interquartile range (IQR)3.4214373 × 108

Descriptive statistics

Standard deviation4.9083575 × 108
Coefficient of variation (CV)1.623286
Kurtosis9.7166278
Mean3.0237171 × 108
Median Absolute Deviation (MAD)1.205337 × 108
Skewness2.9225271
Sum2.5399223 × 1010
Variance2.4091974 × 1017
MonotonicityNot monotonic
2024-01-29T01:36:18.332747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100973900 1
 
1.2%
155025680 1
 
1.2%
16531170 1
 
1.2%
56863090 1
 
1.2%
43744590 1
 
1.2%
256888200 1
 
1.2%
1399130900 1
 
1.2%
270344250 1
 
1.2%
445291310 1
 
1.2%
437610010 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
95040 1
1.2%
214000 1
1.2%
281730 1
1.2%
331190 1
1.2%
421750 1
1.2%
529950 1
1.2%
605730 1
1.2%
1120230 1
1.2%
1174010 1
1.2%
1587200 1
1.2%
ValueCountFrequency (%)
2654266100 1
1.2%
2403829200 1
1.2%
1549458740 1
1.2%
1485445410 1
1.2%
1399130900 1
1.2%
1189624720 1
1.2%
1145094640 1
1.2%
846426590 1
1.2%
795551920 1
1.2%
668278320 1
1.2%

Interactions

2024-01-29T01:36:14.784048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.462411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.888818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.324930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.887860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.568982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.996380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.435894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.999443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.668878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.109995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.545408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:15.121466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:13.781207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.222890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T01:36:14.671196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T01:36:18.443009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0650.2600.1810.000
세목명0.0001.0000.0000.4190.2980.4280.711
체납액구간0.0000.0001.0000.0000.3900.0000.534
체납건수0.0650.4190.0001.0000.8180.8930.494
체납금액0.2600.2980.3900.8181.0000.5920.741
누적체납건수0.1810.4280.0000.8930.5921.0000.777
누적체납금액0.0000.7110.5340.4940.7410.7771.000
2024-01-29T01:36:18.567719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간과세년도
세목명1.0000.0000.000
체납액구간0.0001.0000.000
과세년도0.0000.0001.000
2024-01-29T01:36:18.700503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4860.9510.4150.0750.2800.000
체납금액0.4861.0000.5100.9050.1950.1560.174
누적체납건수0.9510.5101.0000.5490.1270.2420.000
누적체납금액0.4150.9050.5491.0000.0000.3180.289
과세년도0.0750.1950.1270.0001.0000.0000.000
세목명0.2800.1560.2420.3180.0001.0000.000
체납액구간0.0000.1740.0000.2890.0000.0001.000

Missing values

2024-01-29T01:36:15.269464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T01:36:15.439899image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
0인천광역시연수구281852020등록면허세10만원 미만1063394592602839100973900
1인천광역시연수구281852020등록면허세10만원~30만원미만34944904605730
2인천광역시연수구281852020자동차세10만원 미만315114353757013830635892820
3인천광역시연수구281852020자동차세10만원~30만원미만2837493547130144332403829200
4인천광역시연수구281852020자동차세30만원~50만원미만20672633860710249332460
5인천광역시연수구281852020자동차세50만원~1백만원미만1690532806539251950
6인천광역시연수구281852020재산세10만원 미만24971422038707050350984460
7인천광역시연수구281852020재산세10만원~30만원미만25934480268804998846426590
8인천광역시연수구281852020재산세1백만원~3백만원미만91146623470246409984620
9인천광역시연수구281852020재산세1억원~3억원미만2297516610121549458740
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
74인천광역시연수구281852021지방소득세5백만원~1천만원미만1610708389021139911240
75인천광역시연수구281852021지방소득세5천만원~1억원미만42536095204253609520
76인천광역시연수구281852021지역자원시설세10만원 미만1010996027281730
77인천광역시연수구281852021취득세10만원 미만195040195040
78인천광역시연수구281852021취득세10만원~30만원미만7117401071174010
79인천광역시연수구281852021취득세1백만원~3백만원미만4584898045848980
80인천광역시연수구281852021취득세1천만원~3천만원미만123426380123426380
81인천광역시연수구281852021취득세30만원~50만원미만4158720041587200
82인천광역시연수구281852021취득세50만원~1백만원미만3187502042610270
83인천광역시연수구281852021취득세5천만원~1억원미만1693646002124198350