Overview

Dataset statistics

Number of variables10
Number of observations208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory86.6 B

Variable types

Categorical6
Numeric4

Dataset

Description지방세 개방형 데이터 구축자료중 2017년 ~ 2021년도에 대한 경상남도 진주시 지방세체납현황에 대한 자료제공입니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15080412

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 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 체납건수High correlation
누적체납금액 is highly overall correlated with 체납금액High correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:00:30.906709
Analysis finished2024-04-06 08:00:35.043652
Duration4.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
경상남도
208 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 208
100.0%

Length

2024-04-06T17:00:35.146628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:35.303175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 208
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
진주시
208 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진주시 208
100.0%

Length

2024-04-06T17:00:35.447266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:35.590966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진주시 208
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
48170
208 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48170
2nd row48170
3rd row48170
4th row48170
5th row48170

Common Values

ValueCountFrequency (%)
48170 208
100.0%

Length

2024-04-06T17:00:35.720752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:35.885258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48170 208
100.0%

과세년도
Categorical

Distinct5
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2020
45 
2021
45 
2018
41 
2019
41 
2017
36 

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 (%)
2020 45
21.6%
2021 45
21.6%
2018 41
19.7%
2019 41
19.7%
2017 36
17.3%

Length

2024-04-06T17:00:36.095983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:36.273665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 45
21.6%
2021 45
21.6%
2018 41
19.7%
2019 41
19.7%
2017 36
17.3%

세목명
Categorical

Distinct7
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
지방소득세
51 
재산세
48 
취득세
41 
주민세
27 
자동차세
20 
Other values (2)
21 

Length

Max length7
Median length3
Mean length3.9326923
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지방소득세 51
24.5%
재산세 48
23.1%
취득세 41
19.7%
주민세 27
13.0%
자동차세 20
 
9.6%
지역자원시설세 15
 
7.2%
등록면허세 6
 
2.9%

Length

2024-04-06T17:00:36.516488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:00:36.738358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지방소득세 51
24.5%
재산세 48
23.1%
취득세 41
19.7%
주민세 27
13.0%
자동차세 20
 
9.6%
지역자원시설세 15
 
7.2%
등록면허세 6
 
2.9%

체납액구간
Categorical

Distinct11
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
10만원 미만
35 
10만원~30만원미만
29 
30만원~50만원미만
28 
50만원~1백만원미만
26 
1백만원~3백만원미만
22 
Other values (6)
68 

Length

Max length11
Median length11
Mean length10.245192
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
16.8%
10만원~30만원미만 29
13.9%
30만원~50만원미만 28
13.5%
50만원~1백만원미만 26
12.5%
1백만원~3백만원미만 22
10.6%
1천만원~3천만원미만 15
7.2%
3백만원~5백만원미만 15
7.2%
5백만원~1천만원미만 15
7.2%
3천만원~5천만원미만 10
 
4.8%
5천만원~1억원미만 9
 
4.3%

Length

2024-04-06T17:00:36.987807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 35
14.4%
미만 35
14.4%
10만원~30만원미만 29
11.9%
30만원~50만원미만 28
11.5%
50만원~1백만원미만 26
10.7%
1백만원~3백만원미만 22
9.1%
1천만원~3천만원미만 15
6.2%
3백만원~5백만원미만 15
6.2%
5백만원~1천만원미만 15
6.2%
3천만원~5천만원미만 10
 
4.1%
Other values (2) 13
 
5.3%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean533.57692
Minimum1
Maximum14878
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T17:00:37.205745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median14
Q3113.5
95-th percentile3930.2
Maximum14878
Range14877
Interquartile range (IQR)110.5

Descriptive statistics

Standard deviation1757.5488
Coefficient of variation (CV)3.2938995
Kurtosis37.313089
Mean533.57692
Median Absolute Deviation (MAD)13
Skewness5.5275679
Sum110984
Variance3088977.7
MonotonicityNot monotonic
2024-04-06T17:00:37.433353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 21
 
10.1%
1 21
 
10.1%
3 12
 
5.8%
5 12
 
5.8%
4 8
 
3.8%
7 8
 
3.8%
14 5
 
2.4%
12 4
 
1.9%
8 4
 
1.9%
6 4
 
1.9%
Other values (90) 109
52.4%
ValueCountFrequency (%)
1 21
10.1%
2 21
10.1%
3 12
5.8%
4 8
 
3.8%
5 12
5.8%
6 4
 
1.9%
7 8
 
3.8%
8 4
 
1.9%
9 1
 
0.5%
10 2
 
1.0%
ValueCountFrequency (%)
14878 1
0.5%
13817 1
0.5%
6744 1
0.5%
5010 1
0.5%
4856 1
0.5%
4817 1
0.5%
4809 1
0.5%
4432 1
0.5%
4100 1
0.5%
3985 1
0.5%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87804290
Minimum70020
Maximum7.0433086 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T17:00:37.663502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70020
5-th percentile421167.5
Q14676637.5
median32768990
Q31.1755636 × 108
95-th percentile3.1985383 × 108
Maximum7.0433086 × 108
Range7.0426084 × 108
Interquartile range (IQR)1.1287972 × 108

Descriptive statistics

Standard deviation1.3036656 × 108
Coefficient of variation (CV)1.4847402
Kurtosis8.2026969
Mean87804290
Median Absolute Deviation (MAD)31730750
Skewness2.6283718
Sum1.8263292 × 1010
Variance1.699544 × 1016
MonotonicityNot monotonic
2024-04-06T17:00:37.927476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4491230 1
 
0.5%
41531380 1
 
0.5%
237383380 1
 
0.5%
10614360 1
 
0.5%
3780710 1
 
0.5%
4858870 1
 
0.5%
3911290 1
 
0.5%
28571150 1
 
0.5%
59772630 1
 
0.5%
157363800 1
 
0.5%
Other values (198) 198
95.2%
ValueCountFrequency (%)
70020 1
0.5%
116450 1
0.5%
158890 1
0.5%
183730 1
0.5%
204750 1
0.5%
224090 1
0.5%
274620 1
0.5%
278100 1
0.5%
282330 1
0.5%
350530 1
0.5%
ValueCountFrequency (%)
704330860 1
0.5%
691146930 1
0.5%
672675040 1
0.5%
662763430 1
0.5%
614421520 1
0.5%
445021470 1
0.5%
431711710 1
0.5%
405485530 1
0.5%
369244880 1
0.5%
331026240 1
0.5%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct142
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1741.226
Minimum1
Maximum37320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T17:00:38.154408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q117
median64.5
Q3356
95-th percentile12071.75
Maximum37320
Range37319
Interquartile range (IQR)339

Descriptive statistics

Standard deviation5276.9838
Coefficient of variation (CV)3.030614
Kurtosis19.519171
Mean1741.226
Median Absolute Deviation (MAD)58
Skewness4.1565898
Sum362175
Variance27846558
MonotonicityNot monotonic
2024-04-06T17:00:38.400821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 10
 
4.8%
3 6
 
2.9%
8 5
 
2.4%
4 5
 
2.4%
1 4
 
1.9%
21 4
 
1.9%
6 3
 
1.4%
39 3
 
1.4%
33 3
 
1.4%
12 3
 
1.4%
Other values (132) 162
77.9%
ValueCountFrequency (%)
1 4
 
1.9%
2 10
4.8%
3 6
2.9%
4 5
2.4%
5 1
 
0.5%
6 3
 
1.4%
7 3
 
1.4%
8 5
2.4%
9 3
 
1.4%
10 1
 
0.5%
ValueCountFrequency (%)
37320 1
0.5%
34500 1
0.5%
22442 1
0.5%
20280 1
0.5%
19944 1
0.5%
19572 1
0.5%
18952 1
0.5%
15997 1
0.5%
15698 1
0.5%
14755 1
0.5%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8306319 × 108
Minimum253920
Maximum3.3803655 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-06T17:00:38.629028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum253920
5-th percentile1362369.5
Q126945695
median1.0204031 × 108
Q33.5236056 × 108
95-th percentile9.9044589 × 108
Maximum3.3803655 × 109
Range3.3801116 × 109
Interquartile range (IQR)3.2541487 × 108

Descriptive statistics

Standard deviation4.7534236 × 108
Coefficient of variation (CV)1.67928
Kurtosis19.045058
Mean2.8306319 × 108
Median Absolute Deviation (MAD)95274165
Skewness3.8482074
Sum5.8877144 × 1010
Variance2.2595036 × 1017
MonotonicityNot monotonic
2024-04-06T17:00:39.033664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11914680 1
 
0.5%
224028120 1
 
0.5%
568308180 1
 
0.5%
34335010 1
 
0.5%
92280570 1
 
0.5%
11255560 1
 
0.5%
52379440 1
 
0.5%
78819480 1
 
0.5%
180923910 1
 
0.5%
875721430 1
 
0.5%
Other values (198) 198
95.2%
ValueCountFrequency (%)
253920 1
0.5%
366900 1
0.5%
412810 1
0.5%
636900 1
0.5%
717430 1
0.5%
743950 1
0.5%
765230 1
0.5%
781260 1
0.5%
1156710 1
0.5%
1204600 1
0.5%
ValueCountFrequency (%)
3380365540 1
0.5%
3304883310 1
0.5%
2632208270 1
0.5%
1969444840 1
0.5%
1786847150 1
0.5%
1563959310 1
0.5%
1334490400 1
0.5%
1245203300 1
0.5%
1185634290 1
0.5%
1050436580 1
0.5%

Interactions

2024-04-06T17:00:33.786472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:31.411827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:31.999056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.660937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:34.054376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:31.559318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.176947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.804566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:34.241164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:31.706240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.351900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.969827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:34.423867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:31.844172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:32.510256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:00:33.475837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:00:39.185213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
과세년도1.0000.0000.0000.0000.2020.0720.111
세목명0.0001.0000.2410.3840.3700.4240.370
체납액구간0.0000.2411.0000.3080.4550.0000.275
체납건수0.0000.3840.3081.0000.6960.9250.589
체납금액0.2020.3700.4550.6961.0000.6010.793
누적체납건수0.0720.4240.0000.9250.6011.0000.858
누적체납금액0.1110.3700.2750.5890.7930.8581.000
2024-04-06T17:00:39.349725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명과세년도
체납액구간1.0000.1190.000
세목명0.1191.0000.000
과세년도0.0000.0001.000
2024-04-06T17:00:39.526944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액과세년도세목명체납액구간
체납건수1.0000.4350.9450.4250.0000.2400.160
체납금액0.4351.0000.3210.9550.1190.2050.224
누적체납건수0.9450.3211.0000.3740.0410.2420.000
누적체납금액0.4250.9550.3741.0000.0670.2080.132
과세년도0.0000.1190.0410.0671.0000.0000.000
세목명0.2400.2050.2420.2080.0001.0000.119
체납액구간0.1600.2240.0000.1320.0000.1191.000

Missing values

2024-04-06T17:00:34.663953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:00:34.947646image/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
0경상남도진주시481702017등록면허세10만원 미만239449123072011914680
1경상남도진주시481702017자동차세10만원 미만14996878187010037459634850
2경상남도진주시481702017자동차세10만원~30만원미만169527678846096391563959310
3경상남도진주시481702017자동차세30만원~50만원미만451517745028095721120
4경상남도진주시481702017자동차세50만원~1백만원미만528120002919864320
5경상남도진주시481702017재산세10만원 미만972292363903191101952580
6경상남도진주시481702017재산세10만원~30만원미만1332137609049678244270
7경상남도진주시481702017재산세1백만원~3백만원미만254369046064114553700
8경상남도진주시481702017재산세1천만원~3천만원미만3601266608134916000
9경상남도진주시481702017재산세30만원~50만원미만1761267206221607350
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
198경상남도진주시481702021취득세10만원~30만원미만44786251011821591140
199경상남도진주시481702021취득세1백만원~3백만원미만14238158205190313470
200경상남도진주시481702021취득세1억원~3억원미만12201723301220172330
201경상남도진주시481702021취득세1천만원~3천만원미만68941282012179634840
202경상남도진주시481702021취득세30만원~50만원미만72779940218035970
203경상남도진주시481702021취득세3백만원~5백만원미만6224647702179582950
204경상남도진주시481702021취득세3천만원~5천만원미만1366835603109341600
205경상남도진주시481702021취득세50만원~1백만원미만1494481005237576110
206경상남도진주시481702021취득세5백만원~1천만원미만2142639701386467510
207경상남도진주시481702021취득세5천만원~1억원미만1953653302185889180