Overview

Dataset statistics

Number of variables10
Number of observations199
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory86.7 B

Variable types

Categorical6
Numeric4

Dataset

Description부산광역시해운대구_지방세체납현황_20211231
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15078945

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 1 other fieldsHigh correlation
누적체납건수 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
누적체납금액 is highly overall correlated with 체납건수 and 2 other fieldsHigh correlation
체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:28:51.593348
Analysis finished2023-12-10 16:28:53.740924
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
부산광역시
199 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 199
100.0%

Length

2023-12-11T01:28:53.795741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:53.883076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 199
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
해운대구
199 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해운대구 199
100.0%

Length

2023-12-11T01:28:53.964564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:54.050795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해운대구 199
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
26350
199 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26350
2nd row26350
3rd row26350
4th row26350
5th row26350

Common Values

ValueCountFrequency (%)
26350 199
100.0%

Length

2023-12-11T01:28:54.139657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:54.264295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26350 199
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2021
49 
2020
47 
2019
39 
2018
33 
2017
31 

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 49
24.6%
2020 47
23.6%
2019 39
19.6%
2018 33
16.6%
2017 31
15.6%

Length

2023-12-11T01:28:54.374680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:54.490029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 49
24.6%
2020 47
23.6%
2019 39
19.6%
2018 33
16.6%
2017 31
15.6%

세목명
Categorical

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
지방소득세
48 
재산세
42 
취득세
40 
주민세
29 
자동차세
20 
Other values (2)
20 

Length

Max length7
Median length3
Mean length3.8944724
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 48
24.1%
재산세 42
21.1%
취득세 40
20.1%
주민세 29
14.6%
자동차세 20
10.1%
지역자원시설세 11
 
5.5%
등록면허세 9
 
4.5%

Length

2023-12-11T01:28:54.615267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:54.731759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 48
24.1%
재산세 42
21.1%
취득세 40
20.1%
주민세 29
14.6%
자동차세 20
10.1%
지역자원시설세 11
 
5.5%
등록면허세 9
 
4.5%

체납액구간
Categorical

Distinct13
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
10만원 미만
35 
30만원~50만원미만
30 
10만원~30만원미만
27 
50만원~1백만원미만
26 
1백만원~3백만원미만
20 
Other values (8)
61 

Length

Max length11
Median length11
Mean length10.18593
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 35
17.6%
30만원~50만원미만 30
15.1%
10만원~30만원미만 27
13.6%
50만원~1백만원미만 26
13.1%
1백만원~3백만원미만 20
10.1%
3백만원~5백만원미만 17
8.5%
5백만원~1천만원미만 14
 
7.0%
1천만원~3천만원미만 9
 
4.5%
3천만원~5천만원미만 6
 
3.0%
5천만원~1억원미만 5
 
2.5%
Other values (3) 10
 
5.0%

Length

2023-12-11T01:28:54.874970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
15.0%
미만 35
15.0%
30만원~50만원미만 30
12.8%
10만원~30만원미만 27
11.5%
50만원~1백만원미만 26
11.1%
1백만원~3백만원미만 20
8.5%
3백만원~5백만원미만 17
7.3%
5백만원~1천만원미만 14
 
6.0%
1천만원~3천만원미만 9
 
3.8%
3천만원~5천만원미만 6
 
2.6%
Other values (4) 15
6.4%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean805.21608
Minimum1
Maximum20058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T01:28:55.014354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median13
Q3215.5
95-th percentile4299.6
Maximum20058
Range20057
Interquartile range (IQR)212.5

Descriptive statistics

Standard deviation2557.1795
Coefficient of variation (CV)3.1757681
Kurtosis30.787699
Mean805.21608
Median Absolute Deviation (MAD)12
Skewness5.1687371
Sum160238
Variance6539167.2
MonotonicityNot monotonic
2023-12-11T01:28:55.147253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 37
 
18.6%
3 14
 
7.0%
4 12
 
6.0%
2 11
 
5.5%
5 7
 
3.5%
7 4
 
2.0%
6 4
 
2.0%
13 3
 
1.5%
16 2
 
1.0%
12 2
 
1.0%
Other values (92) 103
51.8%
ValueCountFrequency (%)
1 37
18.6%
2 11
 
5.5%
3 14
 
7.0%
4 12
 
6.0%
5 7
 
3.5%
6 4
 
2.0%
7 4
 
2.0%
9 2
 
1.0%
10 2
 
1.0%
11 2
 
1.0%
ValueCountFrequency (%)
20058 1
0.5%
18459 1
0.5%
13201 1
0.5%
11023 1
0.5%
8953 1
0.5%
7346 1
0.5%
6838 1
0.5%
4952 1
0.5%
4839 1
0.5%
4413 1
0.5%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2340056 × 108
Minimum16190
Maximum8.5635943 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T01:28:55.287188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16190
5-th percentile450876
Q14398265
median35303320
Q31.7163834 × 108
95-th percentile5.3913612 × 108
Maximum8.5635943 × 108
Range8.5634324 × 108
Interquartile range (IQR)1.6724007 × 108

Descriptive statistics

Standard deviation1.8839877 × 108
Coefficient of variation (CV)1.5267254
Kurtosis4.1779943
Mean1.2340056 × 108
Median Absolute Deviation (MAD)34750810
Skewness2.1142001
Sum2.4556712 × 1010
Variance3.5494096 × 1016
MonotonicityNot monotonic
2023-12-11T01:28:55.409526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22192960 1
 
0.5%
276742850 1
 
0.5%
776625140 1
 
0.5%
103282010 1
 
0.5%
6488060 1
 
0.5%
312631040 1
 
0.5%
579097890 1
 
0.5%
310322100 1
 
0.5%
238949600 1
 
0.5%
284558660 1
 
0.5%
Other values (189) 189
95.0%
ValueCountFrequency (%)
16190 1
0.5%
22130 1
0.5%
74400 1
0.5%
194110 1
0.5%
223260 1
0.5%
244800 1
0.5%
370800 1
0.5%
392110 1
0.5%
400440 1
0.5%
424020 1
0.5%
ValueCountFrequency (%)
856359430 1
0.5%
838447240 1
0.5%
793643580 1
0.5%
776625140 1
0.5%
766740660 1
0.5%
759874420 1
0.5%
731948280 1
0.5%
622933040 1
0.5%
579097890 1
0.5%
574438970 1
0.5%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct136
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2698.9246
Minimum1
Maximum67774
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T01:28:55.533248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median53
Q3566
95-th percentile16940.9
Maximum67774
Range67773
Interquartile range (IQR)559

Descriptive statistics

Standard deviation8819.6628
Coefficient of variation (CV)3.2678433
Kurtosis31.731023
Mean2698.9246
Median Absolute Deviation (MAD)52
Skewness5.2492166
Sum537086
Variance77786452
MonotonicityNot monotonic
2023-12-11T01:28:55.658048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 18
 
9.0%
2 9
 
4.5%
3 7
 
3.5%
6 6
 
3.0%
4 5
 
2.5%
18 4
 
2.0%
5 4
 
2.0%
19 3
 
1.5%
14 2
 
1.0%
27 2
 
1.0%
Other values (126) 139
69.8%
ValueCountFrequency (%)
1 18
9.0%
2 9
4.5%
3 7
 
3.5%
4 5
 
2.5%
5 4
 
2.0%
6 6
 
3.0%
7 2
 
1.0%
8 1
 
0.5%
10 2
 
1.0%
11 1
 
0.5%
ValueCountFrequency (%)
67774 1
0.5%
65694 1
0.5%
49315 1
0.5%
36114 1
0.5%
25091 1
0.5%
21503 1
0.5%
19985 1
0.5%
19891 1
0.5%
17581 1
0.5%
17453 1
0.5%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct198
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6163805 × 108
Minimum148210
Maximum3.3771078 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T01:28:55.812994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum148210
5-th percentile956343
Q122400510
median82190240
Q33.2948904 × 108
95-th percentile9.5668891 × 108
Maximum3.3771078 × 109
Range3.3769596 × 109
Interquartile range (IQR)3.0708853 × 108

Descriptive statistics

Standard deviation4.5336653 × 108
Coefficient of variation (CV)1.7328005
Kurtosis20.150962
Mean2.6163805 × 108
Median Absolute Deviation (MAD)75973490
Skewness3.9325541
Sum5.2065971 × 1010
Variance2.0554121 × 1017
MonotonicityNot monotonic
2023-12-11T01:28:55.933601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
834300 2
 
1.0%
51259540 1
 
0.5%
229850640 1
 
0.5%
3377107820 1
 
0.5%
372434210 1
 
0.5%
52904260 1
 
0.5%
790849350 1
 
0.5%
1002002430 1
 
0.5%
558066780 1
 
0.5%
324428360 1
 
0.5%
Other values (188) 188
94.5%
ValueCountFrequency (%)
148210 1
0.5%
170340 1
0.5%
244740 1
0.5%
392110 1
0.5%
467800 1
0.5%
500580 1
0.5%
759150 1
0.5%
834300 2
1.0%
915690 1
0.5%
960860 1
0.5%
ValueCountFrequency (%)
3377107820 1
0.5%
2948384350 1
0.5%
2600482680 1
0.5%
1762035440 1
0.5%
1450488260 1
0.5%
1398657000 1
0.5%
1276269400 1
0.5%
1002002430 1
0.5%
977293080 1
0.5%
968538350 1
0.5%

Interactions

2023-12-11T01:28:53.193374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:51.972820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.427165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.819949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:53.296103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.098408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.521324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.921868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:53.379852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.194438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.594785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:53.001471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:53.464288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.312851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:52.701924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:28:53.100533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:28:56.016712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.3180.1570.186
세목명0.0001.0000.1530.3540.3680.5640.321
체납액구간0.0000.1531.0000.0000.6380.0000.000
체납건수0.0000.3540.0001.0000.6550.9530.774
체납금액0.3180.3680.6380.6551.0000.5950.786
누적체납건수0.1570.5640.0000.9530.5951.0000.765
누적체납금액0.1860.3210.0000.7740.7860.7651.000
2023-12-11T01:28:56.108052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도체납액구간세목명
과세년도1.0000.0000.000
체납액구간0.0001.0000.068
세목명0.0000.0681.000
2023-12-11T01:28:56.445181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.5290.9410.6500.0000.1970.000
체납금액0.5291.0000.3490.9530.1380.1950.325
누적체납건수0.9410.3491.0000.5390.0990.2250.000
누적체납금액0.6500.9530.5391.0000.1070.1750.000
과세년도0.0000.1380.0990.1071.0000.0000.000
세목명0.1970.1950.2250.1750.0001.0000.068
체납액구간0.0000.3250.0000.0000.0000.0681.000

Missing values

2023-12-11T01:28:53.576060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:28:53.692977image/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
0부산광역시해운대구263502017등록면허세10만원 미만62722192960150751259540
1부산광역시해운대구263502017자동차세10만원 미만1595701799308768389726940
2부산광역시해운대구263502017자동차세10만원~30만원미만208434625488078651276269400
3부산광역시해운대구263502017자동차세30만원~50만원미만9432051980294102340520
4부산광역시해운대구263502017자동차세50만원~1백만원미만1161473305031566290
5부산광역시해운대구263502017재산세10만원 미만1942627505207298222404790
6부산광역시해운대구263502017재산세10만원~30만원미만26843951330873137278270
7부산광역시해운대구263502017재산세1백만원~3백만원미만20268248306385352290
8부산광역시해운대구263502017재산세30만원~50만원미만30109048109634833710
9부산광역시해운대구263502017재산세50만원~1백만원미만27180708807047442820
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
189부산광역시해운대구263502021취득세10만원~30만원미만7128630011221537890
190부산광역시해운대구263502021취득세1백만원~3백만원미만6119346802954267920
191부산광역시해운대구263502021취득세1천만원~3천만원미만121422480121422480
192부산광역시해운대구263502021취득세30만원~50만원미만51890290176267730
193부산광역시해운대구263502021취득세3백만원~5백만원미만415862740624330360
194부산광역시해운대구263502021취득세3억원~5억원미만13257213401325721340
195부산광역시해운대구263502021취득세50만원~1백만원미만427733005036868910
196부산광역시해운대구263502021취득세5백만원~1천만원미만427163680532548170
197부산광역시해운대구263502021취득세5억원~10억원미만17667406601766740660
198부산광역시해운대구263502021취득세5천만원~1억원미만192846320192846320