Overview

Dataset statistics

Number of variables11
Number of observations126
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory95.0 B

Variable types

Categorical6
Numeric4
DateTime1

Dataset

Description인천광역시 중구에서 부과되는 지방세 체납액에 대한 데이터로 세목명, 체납액구간, 체납건수, 체납금액, 누적체납건수, 누적체납금액 등을 제공합니다.
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079293&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수 and 1 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 11:47:34.461907
Analysis finished2024-01-28 11:47:36.195858
Duration1.73 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
인천광역시
126 

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 126
100.0%

Length

2024-01-28T20:47:36.241896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:47:36.309000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 126
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
중구
126 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 126
100.0%

Length

2024-01-28T20:47:36.383341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:47:36.467682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 126
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
28110
126 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28110
2nd row28110
3rd row28110
4th row28110
5th row28110

Common Values

ValueCountFrequency (%)
28110 126
100.0%

Length

2024-01-28T20:47:36.556616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:47:36.632239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28110 126
100.0%

과세년도
Categorical

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020
44 
2022
43 
2021
39 

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 (%)
2020 44
34.9%
2022 43
34.1%
2021 39
31.0%

Length

2024-01-28T20:47:36.701334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:47:36.775399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 44
34.9%
2022 43
34.1%
2021 39
31.0%

세목명
Categorical

Distinct7
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
재산세
33 
지방소득세
30 
취득세
22 
주민세
18 
자동차세
12 
Other values (2)
11 

Length

Max length7
Median length3
Mean length3.7936508
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 33
26.2%
지방소득세 30
23.8%
취득세 22
17.5%
주민세 18
14.3%
자동차세 12
 
9.5%
등록면허세 8
 
6.3%
지역자원시설세 3
 
2.4%

Length

2024-01-28T20:47:36.864057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:47:36.958585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 33
26.2%
지방소득세 30
23.8%
취득세 22
17.5%
주민세 18
14.3%
자동차세 12
 
9.5%
등록면허세 8
 
6.3%
지역자원시설세 3
 
2.4%

체납액구간
Categorical

Distinct11
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
10만원 미만
21 
10만원~30만원미만
18 
30만원~50만원미만
16 
50만원~1백만원미만
15 
1백만원~3백만원미만
13 
Other values (6)
43 

Length

Max length11
Median length11
Mean length10.206349
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 21
16.7%
10만원~30만원미만 18
14.3%
30만원~50만원미만 16
12.7%
50만원~1백만원미만 15
11.9%
1백만원~3백만원미만 13
10.3%
3백만원~5백만원미만 9
7.1%
1천만원~3천만원미만 8
 
6.3%
5백만원~1천만원미만 8
 
6.3%
3천만원~5천만원미만 7
 
5.6%
5천만원~1억원미만 6
 
4.8%

Length

2024-01-28T20:47:37.068229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 21
14.3%
미만 21
14.3%
10만원~30만원미만 18
12.2%
30만원~50만원미만 16
10.9%
50만원~1백만원미만 15
10.2%
1백만원~3백만원미만 13
8.8%
3백만원~5백만원미만 9
6.1%
1천만원~3천만원미만 8
 
5.4%
5백만원~1천만원미만 8
 
5.4%
3천만원~5천만원미만 7
 
4.8%
Other values (2) 11
7.5%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean620.54762
Minimum1
Maximum9357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T20:47:37.177003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14.25
median18
Q3250.25
95-th percentile3159.5
Maximum9357
Range9356
Interquartile range (IQR)246

Descriptive statistics

Standard deviation1580.3494
Coefficient of variation (CV)2.5467013
Kurtosis14.206434
Mean620.54762
Median Absolute Deviation (MAD)17
Skewness3.6243589
Sum78189
Variance2497504.3
MonotonicityNot monotonic
2024-01-28T20:47:37.281818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14
 
11.1%
13 7
 
5.6%
2 7
 
5.6%
3 6
 
4.8%
5 5
 
4.0%
4 5
 
4.0%
7 5
 
4.0%
16 4
 
3.2%
35 3
 
2.4%
121 2
 
1.6%
Other values (64) 68
54.0%
ValueCountFrequency (%)
1 14
11.1%
2 7
5.6%
3 6
4.8%
4 5
 
4.0%
5 5
 
4.0%
6 1
 
0.8%
7 5
 
4.0%
8 2
 
1.6%
9 1
 
0.8%
10 1
 
0.8%
ValueCountFrequency (%)
9357 1
0.8%
8221 1
0.8%
7564 1
0.8%
5245 1
0.8%
5094 1
0.8%
4883 1
0.8%
3161 1
0.8%
3155 1
0.8%
2610 1
0.8%
2535 1
0.8%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3457053 × 108
Minimum59660
Maximum7.4285321 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T20:47:37.386643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59660
5-th percentile440560
Q18246435
median68778500
Q32.1532681 × 108
95-th percentile4.7813497 × 108
Maximum7.4285321 × 108
Range7.4279355 × 108
Interquartile range (IQR)2.0708037 × 108

Descriptive statistics

Standard deviation1.6269684 × 108
Coefficient of variation (CV)1.209008
Kurtosis2.4257983
Mean1.3457053 × 108
Median Absolute Deviation (MAD)65144075
Skewness1.6061
Sum1.6955887 × 1010
Variance2.6470262 × 1016
MonotonicityNot monotonic
2024-01-28T20:47:37.516100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37728410 1
 
0.8%
280701630 1
 
0.8%
502320220 1
 
0.8%
562532520 1
 
0.8%
213599010 1
 
0.8%
4128180 1
 
0.8%
52433960 1
 
0.8%
383855330 1
 
0.8%
115353800 1
 
0.8%
311060 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
59660 1
0.8%
110670 1
0.8%
241560 1
0.8%
283880 1
0.8%
311060 1
0.8%
355510 1
0.8%
389950 1
0.8%
592390 1
0.8%
864950 1
0.8%
925580 1
0.8%
ValueCountFrequency (%)
742853210 1
0.8%
727271140 1
0.8%
576334520 1
0.8%
562532520 1
0.8%
558239120 1
0.8%
502320220 1
0.8%
484013790 1
0.8%
460498510 1
0.8%
442408780 1
0.8%
413636040 1
0.8%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct86
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1313.4048
Minimum1
Maximum17209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T20:47:37.639781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median36.5
Q3458.75
95-th percentile7564
Maximum17209
Range17208
Interquartile range (IQR)451.75

Descriptive statistics

Standard deviation3230.6664
Coefficient of variation (CV)2.4597645
Kurtosis11.093208
Mean1313.4048
Median Absolute Deviation (MAD)35.5
Skewness3.2252058
Sum165489
Variance10437205
MonotonicityNot monotonic
2024-01-28T20:47:37.744441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 10
 
7.9%
7 6
 
4.8%
5 6
 
4.8%
4 5
 
4.0%
16 5
 
4.0%
2 4
 
3.2%
13 3
 
2.4%
3 3
 
2.4%
31 2
 
1.6%
39 2
 
1.6%
Other values (76) 80
63.5%
ValueCountFrequency (%)
1 10
7.9%
2 4
 
3.2%
3 3
 
2.4%
4 5
4.0%
5 6
4.8%
6 1
 
0.8%
7 6
4.8%
8 1
 
0.8%
9 1
 
0.8%
10 2
 
1.6%
ValueCountFrequency (%)
17209 1
0.8%
16346 1
0.8%
16332 1
0.8%
9395 1
0.8%
8822 1
0.8%
7694 1
0.8%
7595 1
0.8%
7471 1
0.8%
7075 1
0.8%
7000 1
0.8%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1435349 × 108
Minimum59660
Maximum2.124717 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T20:47:37.851347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59660
5-th percentile866335
Q118159870
median86591135
Q34.9985462 × 108
95-th percentile1.2200017 × 109
Maximum2.124717 × 109
Range2.1246573 × 109
Interquartile range (IQR)4.8169475 × 108

Descriptive statistics

Standard deviation4.4998763 × 108
Coefficient of variation (CV)1.4314701
Kurtosis2.7227819
Mean3.1435349 × 108
Median Absolute Deviation (MAD)84382930
Skewness1.7801207
Sum3.960854 × 1010
Variance2.0248886 × 1017
MonotonicityNot monotonic
2024-01-28T20:47:37.951137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106894300 1
 
0.8%
683703910 1
 
0.8%
1024314280 1
 
0.8%
1174469810 1
 
0.8%
602201220 1
 
0.8%
29735720 1
 
0.8%
165582250 1
 
0.8%
1240731080 1
 
0.8%
295667490 1
 
0.8%
311060 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
59660 1
0.8%
110670 1
0.8%
241560 1
0.8%
283880 1
0.8%
311060 1
0.8%
529000 1
0.8%
864950 1
0.8%
870490 1
0.8%
925580 1
0.8%
931870 1
0.8%
ValueCountFrequency (%)
2124716970 1
0.8%
1782366350 1
0.8%
1635073260 1
0.8%
1618342770 1
0.8%
1339238930 1
0.8%
1240731080 1
0.8%
1227144640 1
0.8%
1198572720 1
0.8%
1192523410 1
0.8%
1174469810 1
0.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2024-01-28T20:47:38.031425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:38.098745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-28T20:47:35.550320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:34.764178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.018903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.285685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.606918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:34.828063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.079691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.355469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.672824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:34.894450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.158356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.424479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.737094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:34.961951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.225493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:47:35.489107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:47:38.154178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.0000.7050.5320.5590.573
체납액구간0.0000.0001.0000.4460.4130.3770.582
체납건수0.0000.7050.4461.0000.6330.9190.594
체납금액0.0000.5320.4130.6331.0000.6350.833
누적체납건수0.0000.5590.3770.9190.6351.0000.632
누적체납금액0.0000.5730.5820.5940.8330.6321.000
2024-01-28T20:47:38.234676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간과세년도
세목명1.0000.0000.000
체납액구간0.0001.0000.000
과세년도0.0000.0001.000
2024-01-28T20:47:38.301168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4640.9670.4700.0000.3130.234
체납금액0.4641.0000.4930.9670.0000.3150.199
누적체납건수0.9670.4931.0000.5480.0000.3730.198
누적체납금액0.4700.9670.5481.0000.0000.3320.291
과세년도0.0000.0000.0000.0001.0000.0000.000
세목명0.3130.3150.3730.3320.0001.0000.000
체납액구간0.2340.1990.1980.2910.0000.0001.000

Missing values

2024-01-28T20:47:35.820940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:47:35.937379image/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

시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일
0인천광역시중구281102020등록면허세10만원 미만10473772841029891068943002022-12-31
1인천광역시중구281102020등록면허세10만원~30만원미만238995035290002022-12-31
2인천광역시중구281102020자동차세10만원 미만250410964719074713309704502022-12-31
3인천광역시중구281102020자동차세10만원~30만원미만2137375130200769413392389302022-12-31
4인천광역시중구281102020자동차세30만원~50만원미만114395956204461539127302022-12-31
5인천광역시중구281102020자동차세50만원~1백만원미만4209923036227603602022-12-31
6인천광역시중구281102020재산세10만원 미만5094209106430172096328609302022-12-31
7인천광역시중구281102020재산세10만원~30만원미만3161558239120624211040020402022-12-31
8인천광역시중구281102020재산세1백만원~3백만원미만1702855886204938189585802022-12-31
9인천광역시중구281102020재산세1억원~3억원미만47428532101021247169702022-12-31
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액데이터기준일
116인천광역시중구281102022지방소득세5천만원~1억원미만212394351021239435102022-12-31
117인천광역시중구281102022지역자원시설세10만원 미만7596607596602022-12-31
118인천광역시중구281102022취득세10만원 미만17931870179318702022-12-31
119인천광역시중구281102022취득세10만원~30만원미만1521624601521624602022-12-31
120인천광역시중구281102022취득세1백만원~3백만원미만101850907010185090702022-12-31
121인천광역시중구281102022취득세1억원~3억원미만123704227012370422702022-12-31
122인천광역시중구281102022취득세30만원~50만원미만52091910520919102022-12-31
123인천광역시중구281102022취득세3백만원~5백만원미만5194360005194360002022-12-31
124인천광역시중구281102022취득세50만원~1백만원미만43140670431406702022-12-31
125인천광역시중구281102022취득세5천만원~1억원미만1782946301782946302022-12-31