Overview

Dataset statistics

Number of variables10
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory87.6 B

Variable types

Categorical6
Numeric4

Dataset

Description부산광역시연제구_지방세체납현황_20211021
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15079357

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 started2023-12-10 17:02:30.817947
Analysis finished2023-12-10 17:02:33.996062
Duration3.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
부산광역시
81 

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 81
100.0%

Length

2023-12-11T02:02:34.108830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:34.272899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 81
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
연제구
81 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연제구 81
100.0%

Length

2023-12-11T02:02:34.467398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:34.660024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 81
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
26470
81 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26470
2nd row26470
3rd row26470
4th row26470
5th row26470

Common Values

ValueCountFrequency (%)
26470 81
100.0%

Length

2023-12-11T02:02:34.855229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:35.015765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 81
100.0%

과세년도
Categorical

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size780.0 B
2019
31 
2018
27 
2017
23 

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 (%)
2019 31
38.3%
2018 27
33.3%
2017 23
28.4%

Length

2023-12-11T02:02:35.187832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:35.383687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 31
38.3%
2018 27
33.3%
2017 23
28.4%

세목명
Categorical

Distinct7
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size780.0 B
재산세
19 
지방소득세
19 
취득세
16 
자동차세
11 
주민세
9 
Other values (2)
7 

Length

Max length7
Median length3
Mean length3.8518519
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 19
23.5%
지방소득세 19
23.5%
취득세 16
19.8%
자동차세 11
13.6%
주민세 9
11.1%
등록면허세 4
 
4.9%
지역자원시설세 3
 
3.7%

Length

2023-12-11T02:02:35.629836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:35.873403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 19
23.5%
지방소득세 19
23.5%
취득세 16
19.8%
자동차세 11
13.6%
주민세 9
11.1%
등록면허세 4
 
4.9%
지역자원시설세 3
 
3.7%

체납액구간
Categorical

Distinct8
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size780.0 B
10만원 미만
20 
10만원~30만원미만
15 
30만원~50만원미만
15 
50만원~1백만원미만
11 
1백만원~3백만원미만
8 
Other values (3)
12 

Length

Max length11
Median length11
Mean length10.012346
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10만원 미만 20
24.7%
10만원~30만원미만 15
18.5%
30만원~50만원미만 15
18.5%
50만원~1백만원미만 11
13.6%
1백만원~3백만원미만 8
 
9.9%
3백만원~5백만원미만 7
 
8.6%
1천만원~3천만원미만 3
 
3.7%
5백만원~1천만원미만 2
 
2.5%

Length

2023-12-11T02:02:36.179848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:02:36.434318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10만원 20
19.8%
미만 20
19.8%
10만원~30만원미만 15
14.9%
30만원~50만원미만 15
14.9%
50만원~1백만원미만 11
10.9%
1백만원~3백만원미만 8
 
7.9%
3백만원~5백만원미만 7
 
6.9%
1천만원~3천만원미만 3
 
3.0%
5백만원~1천만원미만 2
 
2.0%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean408.64198
Minimum1
Maximum7032
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-11T02:02:36.700791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median11
Q3165
95-th percentile1450
Maximum7032
Range7031
Interquartile range (IQR)163

Descriptive statistics

Standard deviation1206.2475
Coefficient of variation (CV)2.9518444
Kurtosis19.557018
Mean408.64198
Median Absolute Deviation (MAD)10
Skewness4.349205
Sum33100
Variance1455033.1
MonotonicityNot monotonic
2023-12-11T02:02:36.975741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 19
23.5%
2 8
 
9.9%
3 4
 
4.9%
4 4
 
4.9%
7 2
 
2.5%
9 2
 
2.5%
257 1
 
1.2%
33 1
 
1.2%
42 1
 
1.2%
415 1
 
1.2%
Other values (38) 38
46.9%
ValueCountFrequency (%)
1 19
23.5%
2 8
9.9%
3 4
 
4.9%
4 4
 
4.9%
6 1
 
1.2%
7 2
 
2.5%
9 2
 
2.5%
11 1
 
1.2%
12 1
 
1.2%
15 1
 
1.2%
ValueCountFrequency (%)
7032 1
1.2%
6215 1
1.2%
5104 1
1.2%
2226 1
1.2%
1450 1
1.2%
1398 1
1.2%
1263 1
1.2%
1110 1
1.2%
926 1
1.2%
906 1
1.2%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27305847
Minimum7210
Maximum3.8276324 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-11T02:02:37.237378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7210
5-th percentile242680
Q11467730
median10179620
Q324354810
95-th percentile1.2129544 × 108
Maximum3.8276324 × 108
Range3.8275603 × 108
Interquartile range (IQR)22887080

Descriptive statistics

Standard deviation55336288
Coefficient of variation (CV)2.0265362
Kurtosis23.125151
Mean27305847
Median Absolute Deviation (MAD)9319230
Skewness4.3609805
Sum2.2117736 × 109
Variance3.0621048 × 1015
MonotonicityNot monotonic
2023-12-11T02:02:37.966741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9372420 1
 
1.2%
16436620 1
 
1.2%
24970960 1
 
1.2%
11659250 1
 
1.2%
11531600 1
 
1.2%
78466080 1
 
1.2%
60102750 1
 
1.2%
1583020 1
 
1.2%
40127340 1
 
1.2%
382763240 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
7210 1
1.2%
42920 1
1.2%
68010 1
1.2%
73900 1
1.2%
242680 1
1.2%
293320 1
1.2%
306690 1
1.2%
365000 1
1.2%
379230 1
1.2%
485100 1
1.2%
ValueCountFrequency (%)
382763240 1
1.2%
232751540 1
1.2%
146301610 1
1.2%
144113410 1
1.2%
121295440 1
1.2%
95281560 1
1.2%
78466080 1
1.2%
68329110 1
1.2%
64565610 1
1.2%
60102750 1
1.2%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct59
Distinct (%)72.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1433.4815
Minimum1
Maximum26632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-11T02:02:38.257236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110
median42
Q3502
95-th percentile6998
Maximum26632
Range26631
Interquartile range (IQR)492

Descriptive statistics

Standard deviation4153.2762
Coefficient of variation (CV)2.8973351
Kurtosis21.219613
Mean1433.4815
Median Absolute Deviation (MAD)40
Skewness4.3577235
Sum116112
Variance17249703
MonotonicityNot monotonic
2023-12-11T02:02:38.531664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5
 
6.2%
13 3
 
3.7%
21 3
 
3.7%
3 3
 
3.7%
42 3
 
3.7%
2 3
 
3.7%
11 2
 
2.5%
5 2
 
2.5%
6 2
 
2.5%
4 2
 
2.5%
Other values (49) 53
65.4%
ValueCountFrequency (%)
1 5
6.2%
2 3
3.7%
3 3
3.7%
4 2
 
2.5%
5 2
 
2.5%
6 2
 
2.5%
7 1
 
1.2%
8 2
 
2.5%
10 2
 
2.5%
11 2
 
2.5%
ValueCountFrequency (%)
26632 1
1.2%
19600 1
1.2%
13385 1
1.2%
8345 1
1.2%
6998 1
1.2%
6895 1
1.2%
5785 1
1.2%
4772 1
1.2%
4275 1
1.2%
3374 1
1.2%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82291909
Minimum73900
Maximum1.1488028 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-11T02:02:38.762506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73900
5-th percentile2120340
Q17912130
median19508400
Q361267550
95-th percentile3.530003 × 108
Maximum1.1488028 × 109
Range1.1487289 × 109
Interquartile range (IQR)53355420

Descriptive statistics

Standard deviation1.7602794 × 108
Coefficient of variation (CV)2.1390673
Kurtosis19.245639
Mean82291909
Median Absolute Deviation (MAD)16043350
Skewness4.0493051
Sum6.6656446 × 109
Variance3.0985834 × 1016
MonotonicityNot monotonic
2023-12-11T02:02:39.020433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18612410 1
 
1.2%
27762130 1
 
1.2%
39622880 1
 
1.2%
11659250 1
 
1.2%
19508400 1
 
1.2%
155212790 1
 
1.2%
170062140 1
 
1.2%
12700620 1
 
1.2%
90218020 1
 
1.2%
1148802820 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
73900 1
1.2%
141910 1
1.2%
149120 1
1.2%
1787900 1
1.2%
2120340 1
1.2%
2499570 1
1.2%
2619290 1
1.2%
3253790 1
1.2%
3456980 1
1.2%
3465050 1
1.2%
ValueCountFrequency (%)
1148802820 1
1.2%
766039580 1
1.2%
533288040 1
1.2%
483063050 1
1.2%
353000300 1
1.2%
338949640 1
1.2%
288434690 1
1.2%
240110350 1
1.2%
217654200 1
1.2%
170062140 1
1.2%

Interactions

2023-12-11T02:02:33.073691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:31.287963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:31.905646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.523392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:33.218879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:31.456465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.063927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.660125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:33.386017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:31.637343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.219197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.811589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:33.529958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:31.763151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.368570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:02:32.933576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:02:39.193152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.0000.0000.098
세목명0.0001.0000.0000.5420.2520.5780.298
체납액구간0.0000.0001.0000.0000.0000.0000.000
체납건수0.0000.5420.0001.0000.8500.9980.973
체납금액0.0000.2520.0000.8501.0000.7850.919
누적체납건수0.0000.5780.0000.9980.7851.0000.963
누적체납금액0.0980.2980.0000.9730.9190.9631.000
2023-12-11T02:02:39.375388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명과세년도
체납액구간1.0000.0000.000
세목명0.0001.0000.000
과세년도0.0000.0001.000
2023-12-11T02:02:39.548475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.7670.9210.8250.0000.2120.000
체납금액0.7671.0000.6290.9400.0000.1530.000
누적체납건수0.9210.6291.0000.7740.0000.2310.000
누적체납금액0.8250.9400.7741.0000.0640.1090.000
과세년도0.0000.0000.0000.0641.0000.0000.000
세목명0.2120.1530.2310.1090.0001.0000.000
체납액구간0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T02:02:33.702545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:02:33.918308image/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
0부산광역시연제구264702017등록면허세10만원 미만257937242051918612410
1부산광역시연제구264702017자동차세10만원 미만858365019405785240110350
2부산광역시연제구264702017자동차세10만원~30만원미만9061463016103374533288040
3부산광역시연제구264702017자동차세30만원~50만원미만2271064509030016110
4부산광역시연제구264702017재산세10만원 미만66624354810208670147970
5부산광역시연제구264702017재산세10만원~30만원미만1161838862032547604560
6부산광역시연제구264702017재산세1백만원~3백만원미만1118144056377170
7부산광역시연제구264702017재산세30만원~50만원미만93230710217134310
8부산광역시연제구264702017재산세3백만원~5백만원미만1345698013456980
9부산광역시연제구264702017재산세50만원~1백만원미만2128790031787900
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
71부산광역시연제구264702019지방소득세3백만원~5백만원미만6239088901351751480
72부산광역시연제구264702019지방소득세50만원~1백만원미만6343625720182125046340
73부산광역시연제구264702019지역자원시설세10만원 미만1721011149120
74부산광역시연제구264702019취득세10만원 미만3242680983707730
75부산광역시연제구264702019취득세10만원~30만원미만2365000448583820
76부산광역시연제구264702019취득세1백만원~3백만원미만2381105046430340
77부산광역시연제구264702019취득세30만원~50만원미만2860390134935590
78부산광역시연제구264702019취득세3백만원~5백만원미만417997140832609660
79부산광역시연제구264702019취득세50만원~1백만원미만322146002416829920
80부산광역시연제구264702019취득세5백만원~1천만원미만1504665015046650