Overview

Dataset statistics

Number of variables10
Number of observations202
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.1 KiB
Average record size in memory86.7 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 체납현황을 체납액 규모별로 제공
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078700

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
시군구명 is highly overall correlated with 자치단체코드High correlation
자치단체코드 is highly overall correlated with 시군구명High correlation
체납건수 is highly overall correlated with 누적체납건수High correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:40:02.242111
Analysis finished2023-12-10 23:40:04.771822
Duration2.53 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
창원시
202 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 202
100.0%

Length

2023-12-11T08:40:04.867133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:40:04.966086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 202
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
마산합포구
43 
의창구
43 
성산구
40 
진해구
40 
마산회원구
36 

Length

Max length5
Median length3
Mean length3.7821782
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row성산구
2nd row마산합포구
3rd row마산회원구
4th row진해구
5th row의창구

Common Values

ValueCountFrequency (%)
마산합포구 43
21.3%
의창구 43
21.3%
성산구 40
19.8%
진해구 40
19.8%
마산회원구 36
17.8%

Length

2023-12-11T08:40:05.077677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:40:05.219778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마산합포구 43
21.3%
의창구 43
21.3%
성산구 40
19.8%
진해구 40
19.8%
마산회원구 36
17.8%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
48125
43 
48121
43 
48123
40 
48129
40 
48127
36 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48123
2nd row48125
3rd row48127
4th row48129
5th row48121

Common Values

ValueCountFrequency (%)
48125 43
21.3%
48121 43
21.3%
48123 40
19.8%
48129 40
19.8%
48127 36
17.8%

Length

2023-12-11T08:40:05.345563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:40:05.471936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48125 43
21.3%
48121 43
21.3%
48123 40
19.8%
48129 40
19.8%
48127 36
17.8%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2020
202 

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 202
100.0%

Length

2023-12-11T08:40:05.649824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:40:05.750182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 202
100.0%

세목명
Categorical

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
지방소득세
51 
재산세
47 
취득세
39 
주민세
24 
자동차세
19 
Other values (2)
22 

Length

Max length7
Median length3
Mean length3.9257426
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 51
25.2%
재산세 47
23.3%
취득세 39
19.3%
주민세 24
11.9%
자동차세 19
 
9.4%
등록면허세 11
 
5.4%
지역자원시설세 11
 
5.4%

Length

2023-12-11T08:40:05.884698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:40:06.045379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 51
25.2%
재산세 47
23.3%
취득세 39
19.3%
주민세 24
11.9%
자동차세 19
 
9.4%
등록면허세 11
 
5.4%
지역자원시설세 11
 
5.4%

체납액구간
Categorical

Distinct11
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
10만원 미만
35 
10만원~30만원미만
32 
30만원~50만원미만
27 
50만원~1백만원미만
23 
1백만원~3백만원미만
19 
Other values (6)
66 

Length

Max length11
Median length11
Mean length10.227723
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30만원~50만원미만
2nd row30만원~50만원미만
3rd row30만원~50만원미만
4th row30만원~50만원미만
5th row3백만원~5백만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 35
17.3%
10만원~30만원미만 32
15.8%
30만원~50만원미만 27
13.4%
50만원~1백만원미만 23
11.4%
1백만원~3백만원미만 19
9.4%
3백만원~5백만원미만 16
7.9%
5백만원~1천만원미만 16
7.9%
1천만원~3천만원미만 12
 
5.9%
3천만원~5천만원미만 10
 
5.0%
5천만원~1억원미만 8
 
4.0%

Length

2023-12-11T08:40:06.220860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
14.8%
미만 35
14.8%
10만원~30만원미만 32
13.5%
30만원~50만원미만 27
11.4%
50만원~1백만원미만 23
9.7%
1백만원~3백만원미만 19
8.0%
3백만원~5백만원미만 16
6.8%
5백만원~1천만원미만 16
6.8%
1천만원~3천만원미만 12
 
5.1%
3천만원~5천만원미만 10
 
4.2%
Other values (2) 12
 
5.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean507.9703
Minimum1
Maximum13070
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:06.354918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median16
Q3112.75
95-th percentile2457.15
Maximum13070
Range13069
Interquartile range (IQR)108.75

Descriptive statistics

Standard deviation1569.9742
Coefficient of variation (CV)3.0906811
Kurtosis29.910631
Mean507.9703
Median Absolute Deviation (MAD)15
Skewness5.0642536
Sum102610
Variance2464818.9
MonotonicityNot monotonic
2023-12-11T08:40:06.496903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 26
 
12.9%
3 12
 
5.9%
2 11
 
5.4%
4 11
 
5.4%
6 7
 
3.5%
5 6
 
3.0%
9 5
 
2.5%
10 4
 
2.0%
13 4
 
2.0%
19 4
 
2.0%
Other values (91) 112
55.4%
ValueCountFrequency (%)
1 26
12.9%
2 11
5.4%
3 12
5.9%
4 11
5.4%
5 6
 
3.0%
6 7
 
3.5%
7 2
 
1.0%
8 3
 
1.5%
9 5
 
2.5%
10 4
 
2.0%
ValueCountFrequency (%)
13070 1
0.5%
8604 1
0.5%
8477 1
0.5%
8312 1
0.5%
6917 1
0.5%
4016 1
0.5%
3627 1
0.5%
3276 1
0.5%
2979 1
0.5%
2500 1
0.5%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct202
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76615368
Minimum111240
Maximum5.6323349 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:06.662665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111240
5-th percentile470197
Q14776442.5
median45606370
Q31.1700423 × 108
95-th percentile2.923978 × 108
Maximum5.6323349 × 108
Range5.6312225 × 108
Interquartile range (IQR)1.1222778 × 108

Descriptive statistics

Standard deviation93629111
Coefficient of variation (CV)1.222067
Kurtosis4.9937581
Mean76615368
Median Absolute Deviation (MAD)43606800
Skewness1.9883814
Sum1.5476304 × 1010
Variance8.7664105 × 1015
MonotonicityNot monotonic
2023-12-11T08:40:06.810169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
840780 1
 
0.5%
105129260 1
 
0.5%
1641840 1
 
0.5%
528980 1
 
0.5%
5146700 1
 
0.5%
16652530 1
 
0.5%
1213910 1
 
0.5%
5606250 1
 
0.5%
11691230 1
 
0.5%
43438620 1
 
0.5%
Other values (192) 192
95.0%
ValueCountFrequency (%)
111240 1
0.5%
166860 1
0.5%
184920 1
0.5%
197450 1
0.5%
221310 1
0.5%
320690 1
0.5%
334670 1
0.5%
380840 1
0.5%
404750 1
0.5%
463500 1
0.5%
ValueCountFrequency (%)
563233490 1
0.5%
430047050 1
0.5%
420571330 1
0.5%
334730560 1
0.5%
327744970 1
0.5%
319630730 1
0.5%
316445360 1
0.5%
316338740 1
0.5%
300937540 1
0.5%
296690270 1
0.5%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8906.4158
Minimum1
Maximum140678
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:06.959978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q174
median338
Q31973
95-th percentile55106
Maximum140678
Range140677
Interquartile range (IQR)1899

Descriptive statistics

Standard deviation25378.896
Coefficient of variation (CV)2.8495072
Kurtosis16.445122
Mean8906.4158
Median Absolute Deviation (MAD)326
Skewness3.9303326
Sum1799096
Variance6.4408838 × 108
MonotonicityNot monotonic
2023-12-11T08:40:07.103976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74 5
 
2.5%
232 5
 
2.5%
180 5
 
2.5%
787 5
 
2.5%
94 5
 
2.5%
783 5
 
2.5%
55 5
 
2.5%
420 5
 
2.5%
338 5
 
2.5%
174 5
 
2.5%
Other values (40) 152
75.2%
ValueCountFrequency (%)
1 2
 
1.0%
2 1
 
0.5%
3 2
 
1.0%
4 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
8 5
2.5%
9 1
 
0.5%
10 2
 
1.0%
14 1
 
0.5%
ValueCountFrequency (%)
140678 5
2.5%
61822 5
2.5%
55106 5
2.5%
43379 5
2.5%
18301 5
2.5%
11239 5
2.5%
8090 5
2.5%
4009 5
2.5%
2426 5
2.5%
1988 5
2.5%

누적체납금액
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2840274 × 109
Minimum769410
Maximum1.0350858 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-11T08:40:07.273217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum769410
5-th percentile12372520
Q11.5409681 × 108
median6.7520966 × 108
Q31.8119174 × 109
95-th percentile3.4292928 × 109
Maximum1.0350858 × 1010
Range1.0350089 × 1010
Interquartile range (IQR)1.6578206 × 109

Descriptive statistics

Standard deviation1.8331296 × 109
Coefficient of variation (CV)1.4276406
Kurtosis12.792586
Mean1.2840274 × 109
Median Absolute Deviation (MAD)6.215051 × 108
Skewness3.2007397
Sum2.5937353 × 1011
Variance3.3603641 × 1018
MonotonicityNot monotonic
2023-12-11T08:40:07.442345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28217780 5
 
2.5%
293265930 5
 
2.5%
974965580 5
 
2.5%
1161241270 5
 
2.5%
136378780 5
 
2.5%
36510490 5
 
2.5%
12372520 5
 
2.5%
9711510 5
 
2.5%
17593190 5
 
2.5%
62625850 5
 
2.5%
Other values (43) 152
75.2%
ValueCountFrequency (%)
769410 1
 
0.5%
1097260 1
 
0.5%
1237920 1
 
0.5%
1283520 2
 
1.0%
9711510 5
2.5%
12372520 5
2.5%
12572510 1
 
0.5%
17593190 5
2.5%
25752310 1
 
0.5%
28217780 5
2.5%
ValueCountFrequency (%)
10350857930 5
2.5%
4716737170 5
2.5%
3429292780 5
2.5%
3243543000 5
2.5%
2998203710 5
2.5%
2517260940 5
2.5%
2217473940 5
2.5%
2150723460 5
2.5%
2111071050 5
2.5%
2017933150 4
2.0%

Interactions

2023-12-11T08:40:04.138509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:02.633648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.320247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.723384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:04.239624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:02.734406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.410191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.829705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:04.342613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:02.818100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.502384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.947065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:04.437630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:02.915171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:03.614694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:40:04.046347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:40:07.561873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드세목명체납액구간체납건수체납금액누적체납건수누적체납금액
시군구명1.0001.0000.0000.0000.1010.0000.0000.000
자치단체코드1.0001.0000.0000.0000.1010.0000.0000.000
세목명0.0000.0001.0000.1570.5890.4190.5310.580
체납액구간0.0000.0000.1571.0000.2280.4570.5550.687
체납건수0.1010.1010.5890.2281.0000.6020.8200.514
체납금액0.0000.0000.4190.4570.6021.0000.6490.661
누적체납건수0.0000.0000.5310.5550.8200.6491.0000.733
누적체납금액0.0000.0000.5800.6870.5140.6610.7331.000
2023-12-11T08:40:07.698101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드체납액구간세목명
시군구명1.0001.0000.0000.000
자치단체코드1.0001.0000.0000.000
체납액구간0.0000.0001.0000.075
세목명0.0000.0000.0751.000
2023-12-11T08:40:07.816602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액시군구명자치단체코드세목명체납액구간
체납건수1.0000.4210.9370.4540.0630.0630.2390.112
체납금액0.4211.0000.2840.9190.0000.0000.2400.232
누적체납건수0.9370.2841.0000.4160.0000.0000.3740.341
누적체납금액0.4540.9190.4161.0000.0000.0000.3930.436
시군구명0.0630.0000.0000.0001.0001.0000.0000.000
자치단체코드0.0630.0000.0000.0001.0001.0000.0000.000
세목명0.2390.2400.3740.3930.0000.0001.0000.075
체납액구간0.1120.2320.3410.4360.0000.0000.0751.000

Missing values

2023-12-11T08:40:04.553905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:40:04.717775image/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
0창원시성산구481232020취득세30만원~50만원미만28407807428217780
1창원시마산합포구481252020취득세30만원~50만원미만417052407428217780
2창원시마산회원구481272020취득세30만원~50만원미만28725607428217780
3창원시진해구481292020취득세30만원~50만원미만619984107428217780
4창원시의창구481212020취득세3백만원~5백만원미만31038691047184005600
5창원시성산구481232020취득세3백만원~5백만원미만73237125047184005600
6창원시마산합포구481252020취득세3백만원~5백만원미만2775768047184005600
7창원시마산회원구481272020취득세3백만원~5백만원미만2635527047184005600
8창원시의창구481212020취득세3천만원~5천만원미만2678408209330447420
9창원시의창구481212020취득세50만원~1백만원미만42950110191139093140
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
192창원시의창구481212020지방소득세5백만원~1천만원미만322252006104583243543000
193창원시성산구481232020지방소득세5백만원~1천만원미만221610720504583243543000
194창원시마산합포구481252020지방소득세5백만원~1천만원미만161072921304583243543000
195창원시마산회원구481272020지방소득세5백만원~1천만원미만231606695304583243543000
196창원시진해구481292020지방소득세5백만원~1천만원미만141002009404583243543000
197창원시의창구481212020지방소득세5천만원~1억원미만3210342930272017933150
198창원시성산구481232020지방소득세5천만원~1억원미만4319630730272017933150
199창원시마산회원구481272020지방소득세5천만원~1억원미만4296690270272017933150
200창원시진해구481292020지방소득세5천만원~1억원미만2143401300272017933150
201창원시의창구481212020지역자원시설세10만원 미만109122546078312372520