Overview

Dataset statistics

Number of variables10
Number of observations170
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.4 KiB
Average record size in memory86.8 B

Variable types

Categorical6
Numeric4

Dataset

Description인천광역시 서구 2017년도부터 2021년도까지 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액을 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15078591&srcSe=7661IVAWM27C61E190

Alerts

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

Reproduction

Analysis started2024-01-28 10:37:26.030752
Analysis finished2024-01-28 10:37:27.573003
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
인천광역시
170 

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 170
100.0%

Length

2024-01-28T19:37:27.623225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:37:27.705421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 170
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
서구
170 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 170
100.0%

Length

2024-01-28T19:37:27.780483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:37:27.854967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 170
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
28260
170 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28260
2nd row28260
3rd row28260
4th row28260
5th row28260

Common Values

ValueCountFrequency (%)
28260 170
100.0%

Length

2024-01-28T19:37:27.937248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:37:28.010288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28260 170
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2021
48 
2020
42 
2019
29 
2017
27 
2018
24 

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 (%)
2021 48
28.2%
2020 42
24.7%
2019 29
17.1%
2017 27
15.9%
2018 24
14.1%

Length

2024-01-28T19:37:28.084533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:37:28.167412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 48
28.2%
2020 42
24.7%
2019 29
17.1%
2017 27
15.9%
2018 24
14.1%

세목명
Categorical

Distinct7
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
재산세
50 
지방소득세
40 
주민세
29 
취득세
21 
자동차세
20 
Other values (2)
10 

Length

Max length7
Median length3
Mean length3.7294118
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 50
29.4%
지방소득세 40
23.5%
주민세 29
17.1%
취득세 21
12.4%
자동차세 20
 
11.8%
등록면허세 8
 
4.7%
지역자원시설세 2
 
1.2%

Length

2024-01-28T19:37:28.263941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:37:28.358260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 50
29.4%
지방소득세 40
23.5%
주민세 29
17.1%
취득세 21
12.4%
자동차세 20
 
11.8%
등록면허세 8
 
4.7%
지역자원시설세 2
 
1.2%

체납액구간
Categorical

Distinct12
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
10만원 미만
29 
10만원~30만원미만
23 
30만원~50만원미만
23 
50만원~1백만원미만
22 
1백만원~3백만원미만
17 
Other values (7)
56 

Length

Max length11
Median length11
Mean length10.217647
Min length7

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row10만원 미만
2nd row10만원 미만
3rd row10만원~30만원미만
4th row30만원~50만원미만
5th row50만원~1백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 29
17.1%
10만원~30만원미만 23
13.5%
30만원~50만원미만 23
13.5%
50만원~1백만원미만 22
12.9%
1백만원~3백만원미만 17
10.0%
3백만원~5백만원미만 13
7.6%
5백만원~1천만원미만 12
7.1%
1천만원~3천만원미만 11
 
6.5%
3천만원~5천만원미만 8
 
4.7%
5천만원~1억원미만 7
 
4.1%
Other values (2) 5
 
2.9%

Length

2024-01-28T19:37:28.477183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 29
14.6%
미만 29
14.6%
10만원~30만원미만 23
11.6%
30만원~50만원미만 23
11.6%
50만원~1백만원미만 22
11.1%
1백만원~3백만원미만 17
8.5%
3백만원~5백만원미만 13
6.5%
5백만원~1천만원미만 12
6.0%
1천만원~3천만원미만 11
 
5.5%
3천만원~5천만원미만 8
 
4.0%
Other values (3) 12
6.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1097.9
Minimum1
Maximum24441
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:37:28.578397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median27.5
Q3376
95-th percentile7419.5
Maximum24441
Range24440
Interquartile range (IQR)371

Descriptive statistics

Standard deviation3236.37
Coefficient of variation (CV)2.9477821
Kurtosis30.385607
Mean1097.9
Median Absolute Deviation (MAD)26.5
Skewness5.0071063
Sum186643
Variance10474090
MonotonicityNot monotonic
2024-01-28T19:37:28.688563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 19
 
11.2%
2 12
 
7.1%
3 9
 
5.3%
5 8
 
4.7%
36 3
 
1.8%
14 3
 
1.8%
18 3
 
1.8%
12 3
 
1.8%
10 3
 
1.8%
22 3
 
1.8%
Other values (91) 104
61.2%
ValueCountFrequency (%)
1 19
11.2%
2 12
7.1%
3 9
5.3%
4 2
 
1.2%
5 8
4.7%
6 1
 
0.6%
8 2
 
1.2%
9 1
 
0.6%
10 3
 
1.8%
11 2
 
1.2%
ValueCountFrequency (%)
24441 1
0.6%
23916 1
0.6%
11373 1
0.6%
9639 1
0.6%
8630 1
0.6%
7737 1
0.6%
7659 1
0.6%
7503 1
0.6%
7460 1
0.6%
7370 1
0.6%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct170
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7934147 × 108
Minimum334870
Maximum1.3860785 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:37:28.786529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum334870
5-th percentile971156
Q17420857.5
median78264315
Q32.1501416 × 108
95-th percentile6.9753832 × 108
Maximum1.3860785 × 109
Range1.3857437 × 109
Interquartile range (IQR)2.075933 × 108

Descriptive statistics

Standard deviation2.7001102 × 108
Coefficient of variation (CV)1.5055694
Kurtosis6.996583
Mean1.7934147 × 108
Median Absolute Deviation (MAD)74197370
Skewness2.4949445
Sum3.0488049 × 1010
Variance7.2905953 × 1016
MonotonicityNot monotonic
2024-01-28T19:37:28.892932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22491440 1
 
0.6%
60782930 1
 
0.6%
265836280 1
 
0.6%
275300740 1
 
0.6%
67479330 1
 
0.6%
820620 1
 
0.6%
1015640 1
 
0.6%
5401500 1
 
0.6%
35558810 1
 
0.6%
152950570 1
 
0.6%
Other values (160) 160
94.1%
ValueCountFrequency (%)
334870 1
0.6%
351750 1
0.6%
469660 1
0.6%
485090 1
0.6%
486670 1
0.6%
694940 1
0.6%
820620 1
0.6%
887880 1
0.6%
934760 1
0.6%
1015640 1
0.6%
ValueCountFrequency (%)
1386078540 1
0.6%
1350658260 1
0.6%
1301700160 1
0.6%
1299919430 1
0.6%
1084981400 1
0.6%
801176740 1
0.6%
770675550 1
0.6%
747823220 1
0.6%
729963340 1
0.6%
657907730 1
0.6%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2773.8353
Minimum1
Maximum34808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:37:28.999952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q117
median88.5
Q3651
95-th percentile22479.2
Maximum34808
Range34807
Interquartile range (IQR)634

Descriptive statistics

Standard deviation7039.1811
Coefficient of variation (CV)2.537707
Kurtosis8.1743459
Mean2773.8353
Median Absolute Deviation (MAD)86.5
Skewness2.9764559
Sum471552
Variance49550071
MonotonicityNot monotonic
2024-01-28T19:37:29.108109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 13
 
7.6%
1 8
 
4.7%
3 7
 
4.1%
5 4
 
2.4%
17 3
 
1.8%
21 2
 
1.2%
23 2
 
1.2%
44 2
 
1.2%
63 2
 
1.2%
27 2
 
1.2%
Other values (119) 125
73.5%
ValueCountFrequency (%)
1 8
4.7%
2 13
7.6%
3 7
4.1%
4 1
 
0.6%
5 4
 
2.4%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
10 1
 
0.6%
11 1
 
0.6%
ValueCountFrequency (%)
34808 1
0.6%
33816 1
0.6%
29266 1
0.6%
28885 1
0.6%
27438 1
0.6%
24762 1
0.6%
24439 1
0.6%
24259 1
0.6%
23030 1
0.6%
21806 1
0.6%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct170
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8690329 × 108
Minimum334870
Maximum5.9536252 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:37:29.218370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum334870
5-th percentile1928716.5
Q118270900
median1.5178084 × 108
Q36.7297822 × 108
95-th percentile1.6811852 × 109
Maximum5.9536252 × 109
Range5.9532903 × 109
Interquartile range (IQR)6.5470732 × 108

Descriptive statistics

Standard deviation8.6781847 × 108
Coefficient of variation (CV)1.782322
Kurtosis19.587276
Mean4.8690329 × 108
Median Absolute Deviation (MAD)1.4607546 × 108
Skewness3.9486938
Sum8.2773559 × 1010
Variance7.5310889 × 1017
MonotonicityNot monotonic
2024-01-28T19:37:29.320648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65920900 1
 
0.6%
60782930 1
 
0.6%
278508880 1
 
0.6%
291795780 1
 
0.6%
67479330 1
 
0.6%
820620 1
 
0.6%
1015640 1
 
0.6%
5736370 1
 
0.6%
36599210 1
 
0.6%
152950570 1
 
0.6%
Other values (160) 160
94.1%
ValueCountFrequency (%)
334870 1
0.6%
351750 1
0.6%
820620 1
0.6%
959440 1
0.6%
960780 1
0.6%
1015640 1
0.6%
1418310 1
0.6%
1445870 1
0.6%
1729020 1
0.6%
2172790 1
0.6%
ValueCountFrequency (%)
5953625150 1
0.6%
5769654130 1
0.6%
4651924990 1
0.6%
3352005560 1
0.6%
2581330010 1
0.6%
2342584510 1
0.6%
2016767450 1
0.6%
1924210120 1
0.6%
1807340490 1
0.6%
1526995400 1
0.6%

Interactions

2024-01-28T19:37:27.122294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.309551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.563256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.847511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:27.183429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.369643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.627900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.912363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:27.252041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.434089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.698087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.984956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:27.319506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.498852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:26.777699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:37:27.056258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:37:29.393835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.2550.0000.075
세목명0.0001.0000.0000.3160.2560.3580.456
체납액구간0.0000.0001.0000.4210.3670.1870.240
체납건수0.0000.3160.4211.0000.8180.8550.661
체납금액0.2550.2560.3670.8181.0000.7250.875
누적체납건수0.0000.3580.1870.8550.7251.0000.864
누적체납금액0.0750.4560.2400.6610.8750.8641.000
2024-01-28T19:37:29.474681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간과세년도
세목명1.0000.0000.000
체납액구간0.0001.0000.000
과세년도0.0000.0001.000
2024-01-28T19:37:29.544171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.5570.9500.5360.0000.1930.173
체납금액0.5571.0000.5290.9140.1570.1410.157
누적체납건수0.9500.5291.0000.6160.0000.1870.076
누적체납금액0.5360.9140.6161.0000.0390.2650.094
과세년도0.0000.1570.0000.0391.0000.0000.000
세목명0.1930.1410.1870.2650.0001.0000.000
체납액구간0.1730.1570.0760.0940.0000.0001.000

Missing values

2024-01-28T19:37:27.416580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:37:27.533071image/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
0인천광역시서구282602017등록면허세10만원 미만71422491440215465920900
1인천광역시서구282602017자동차세10만원 미만268211724162013816617423960
2인천광역시서구282602017자동차세10만원~30만원미만3570594902650153642581330010
3인천광역시서구282602017자동차세30만원~50만원미만15151160220676232047390
4인천광역시서구282602017자동차세50만원~1백만원미만14765217014194910200
5인천광역시서구282602017재산세10만원 미만1807959309806969319547710
6인천광역시서구282602017재산세10만원~30만원미만604936200502313370830780
7인천광역시서구282602017재산세1백만원~3백만원미만64111790780320572679540
8인천광역시서구282602017재산세1천만원~3천만원미만916229495051867697510
9인천광역시서구282602017재산세30만원~50만원미만8830697630298104533660
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
160인천광역시서구282602021취득세10만원 미만442356100442356100
161인천광역시서구282602021취득세10만원~30만원미만467010030467010030
162인천광역시서구282602021취득세1백만원~3백만원미만28430185603045750430
163인천광역시서구282602021취득세1천만원~3천만원미만341409640341409640
164인천광역시서구282602021취득세30만원~50만원미만177369850177369850
165인천광역시서구282602021취득세3백만원~5백만원미만2410918454024109184540
166인천광역시서구282602021취득세3천만원~5천만원미만31054311203105431120
167인천광역시서구282602021취득세50만원~1백만원미만22152250902517055130
168인천광역시서구282602021취득세5백만원~1천만원미만2718656935027186569350
169인천광역시서구282602021취득세5천만원~1억원미만1745152702145934750