Overview

Dataset statistics

Number of variables10
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory88.5 B

Variable types

Categorical6
Numeric4

Dataset

Description제주특별자치도 제주시 지방세 체납액 규모별 체납 건수를 납세자 유형별로 제공합니다. 체납정책 수립시 기초자료로 활용할 수 있습니다.
Author제주특별자치도 제주시
URLhttps://www.data.go.kr/data/15078984/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
체납건수 is highly overall correlated with 누적체납건수 and 1 other fieldsHigh correlation
체납금액 is highly overall correlated with 누적체납금액High correlation
누적체납건수 is highly overall correlated with 체납건수High correlation
누적체납금액 is highly overall correlated with 체납건수 and 1 other fieldsHigh correlation
체납금액 has unique valuesUnique
누적체납금액 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:16:22.910961
Analysis finished2023-12-12 13:16:25.246982
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
제주특별자치도
52 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주특별자치도 52
100.0%

Length

2023-12-12T22:16:25.322734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:25.411322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 52
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
제주시
52 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 52
100.0%

Length

2023-12-12T22:16:25.514511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:25.609494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 52
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
50110
52 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50110
2nd row50110
3rd row50110
4th row50110
5th row50110

Common Values

ValueCountFrequency (%)
50110 52
100.0%

Length

2023-12-12T22:16:25.721882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:25.822342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50110 52
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2020
52 

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 52
100.0%

Length

2023-12-12T22:16:25.913320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:26.014751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 52
100.0%

세목명
Categorical

Distinct6
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
재산세
12 
지방소득세
11 
취득세
11 
주민세
7 
등록면허세
7 

Length

Max length5
Median length3
Mean length3.7692308
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재산세
2nd row재산세
3rd row재산세
4th row주민세
5th row주민세

Common Values

ValueCountFrequency (%)
재산세 12
23.1%
지방소득세 11
21.2%
취득세 11
21.2%
주민세 7
13.5%
등록면허세 7
13.5%
자동차세 4
 
7.7%

Length

2023-12-12T22:16:26.139275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:16:26.257035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 12
23.1%
지방소득세 11
21.2%
취득세 11
21.2%
주민세 7
13.5%
등록면허세 7
13.5%
자동차세 4
 
7.7%

체납액구간
Categorical

Distinct13
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
10만원 미만
6 
10만원~30만원미만
6 
30만원~50만원미만
6 
50만원~1백만원미만
6 
1백만원~3백만원미만
5 
Other values (8)
23 

Length

Max length11
Median length11
Mean length10.307692
Min length7

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row5백만원~1천만원미만
2nd row5억원~10억원미만
3rd row5천만원~1억원미만
4th row10만원 미만
5th row10만원~30만원미만

Common Values

ValueCountFrequency (%)
10만원 미만 6
11.5%
10만원~30만원미만 6
11.5%
30만원~50만원미만 6
11.5%
50만원~1백만원미만 6
11.5%
1백만원~3백만원미만 5
9.6%
3백만원~5백만원미만 5
9.6%
5백만원~1천만원미만 4
7.7%
1천만원~3천만원미만 4
7.7%
5천만원~1억원미만 3
5.8%
1억원~3억원미만 2
 
3.8%
Other values (3) 5
9.6%

Length

2023-12-12T22:16:26.392705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10만원 6
10.3%
미만 6
10.3%
10만원~30만원미만 6
10.3%
30만원~50만원미만 6
10.3%
50만원~1백만원미만 6
10.3%
1백만원~3백만원미만 5
8.6%
3백만원~5백만원미만 5
8.6%
5백만원~1천만원미만 4
6.9%
1천만원~3천만원미만 4
6.9%
5천만원~1억원미만 3
5.2%
Other values (4) 7
12.1%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1063.9423
Minimum1
Maximum20351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:16:26.543525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.75
median13.5
Q3242
95-th percentile6121.5
Maximum20351
Range20350
Interquartile range (IQR)239.25

Descriptive statistics

Standard deviation3340.1944
Coefficient of variation (CV)3.1394507
Kurtosis23.004297
Mean1063.9423
Median Absolute Deviation (MAD)12.5
Skewness4.5225602
Sum55325
Variance11156899
MonotonicityNot monotonic
2023-12-12T22:16:26.679530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 8
 
15.4%
2 5
 
9.6%
6 4
 
7.7%
50 3
 
5.8%
7 3
 
5.8%
11 2
 
3.8%
14 2
 
3.8%
9 2
 
3.8%
6127 1
 
1.9%
4254 1
 
1.9%
Other values (21) 21
40.4%
ValueCountFrequency (%)
1 8
15.4%
2 5
9.6%
3 1
 
1.9%
6 4
7.7%
7 3
 
5.8%
9 2
 
3.8%
11 2
 
3.8%
13 1
 
1.9%
14 2
 
3.8%
15 1
 
1.9%
ValueCountFrequency (%)
20351 1
1.9%
10509 1
1.9%
6127 1
1.9%
6117 1
1.9%
4254 1
1.9%
2201 1
1.9%
1890 1
1.9%
802 1
1.9%
734 1
1.9%
515 1
1.9%

체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5149516 × 108
Minimum292890
Maximum1.5027191 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:16:26.872526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum292890
5-th percentile783483.5
Q110386700
median1.156539 × 108
Q33.4914926 × 108
95-th percentile1.0808785 × 109
Maximum1.5027191 × 109
Range1.5024262 × 109
Interquartile range (IQR)3.3876256 × 108

Descriptive statistics

Standard deviation3.4210459 × 108
Coefficient of variation (CV)1.360283
Kurtosis3.5896841
Mean2.5149516 × 108
Median Absolute Deviation (MAD)1.1290746 × 108
Skewness1.9357422
Sum1.3077748 × 1010
Variance1.1703555 × 1017
MonotonicityNot monotonic
2023-12-12T22:16:27.024801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350829790 1
 
1.9%
26330050 1
 
1.9%
7040980 1
 
1.9%
71029030 1
 
1.9%
62766500 1
 
1.9%
40634260 1
 
1.9%
897770 1
 
1.9%
2321610 1
 
1.9%
55239650 1
 
1.9%
643800 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
292890 1
1.9%
530390 1
1.9%
643800 1
1.9%
897770 1
1.9%
1924170 1
1.9%
2268530 1
1.9%
2321610 1
1.9%
3171260 1
1.9%
3570460 1
1.9%
6255970 1
1.9%
ValueCountFrequency (%)
1502719080 1
1.9%
1107743770 1
1.9%
1087207020 1
1.9%
1075700670 1
1.9%
850657260 1
1.9%
718197050 1
1.9%
553357110 1
1.9%
543567420 1
1.9%
443628030 1
1.9%
428127700 1
1.9%

누적체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2361.8269
Minimum1
Maximum42364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:16:27.503947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.55
Q16.5
median36
Q3511
95-th percentile16675.95
Maximum42364
Range42363
Interquartile range (IQR)504.5

Descriptive statistics

Standard deviation7333.9622
Coefficient of variation (CV)3.1052073
Kurtosis18.637819
Mean2361.8269
Median Absolute Deviation (MAD)33.5
Skewness4.11769
Sum122815
Variance53787001
MonotonicityNot monotonic
2023-12-12T22:16:27.639101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2 5
 
9.6%
3 4
 
7.7%
1 3
 
5.8%
9 3
 
5.8%
12 2
 
3.8%
54 2
 
3.8%
16 2
 
3.8%
50 2
 
3.8%
35 2
 
3.8%
8524 1
 
1.9%
Other values (26) 26
50.0%
ValueCountFrequency (%)
1 3
5.8%
2 5
9.6%
3 4
7.7%
5 1
 
1.9%
7 1
 
1.9%
9 3
5.8%
12 2
 
3.8%
16 2
 
3.8%
20 1
 
1.9%
21 1
 
1.9%
ValueCountFrequency (%)
42364 1
1.9%
23689 1
1.9%
18222 1
1.9%
15411 1
1.9%
8524 1
1.9%
3971 1
1.9%
3751 1
1.9%
1450 1
1.9%
1070 1
1.9%
733 1
1.9%

누적체납금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9105504 × 108
Minimum1263380
Maximum2.5550643 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T22:16:27.851722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1263380
5-th percentile2525406.5
Q129890035
median1.787073 × 108
Q35.2937626 × 108
95-th percentile1.4327126 × 109
Maximum2.5550643 × 109
Range2.5538009 × 109
Interquartile range (IQR)4.9948622 × 108

Descriptive statistics

Standard deviation5.4372071 × 108
Coefficient of variation (CV)1.3903943
Kurtosis5.5887623
Mean3.9105504 × 108
Median Absolute Deviation (MAD)1.7304727 × 108
Skewness2.2386601
Sum2.0334862 × 1010
Variance2.9563221 × 1017
MonotonicityNot monotonic
2023-12-12T22:16:28.016275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350829790 1
 
1.9%
42403480 1
 
1.9%
35741500 1
 
1.9%
76559640 1
 
1.9%
62766500 1
 
1.9%
81173960 1
 
1.9%
1425430 1
 
1.9%
4735250 1
 
1.9%
69354220 1
 
1.9%
1736030 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1263380 1
1.9%
1425430 1
1.9%
1736030 1
1.9%
3171260 1
1.9%
3267490 1
1.9%
4735250 1
1.9%
8873630 1
1.9%
11566730 1
1.9%
12723970 1
1.9%
14171640 1
1.9%
ValueCountFrequency (%)
2555064300 1
1.9%
2139512430 1
1.9%
1465406190 1
1.9%
1405963270 1
1.9%
1159846260 1
1.9%
1070419800 1
1.9%
909591540 1
1.9%
755686580 1
1.9%
719854970 1
1.9%
700616600 1
1.9%

Interactions

2023-12-12T22:16:24.633489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.245936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.753236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.189354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.735217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.373315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.882191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.300153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.823005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.506677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.986169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.442302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.903833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:23.631080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.076737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:16:24.533365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:16:28.116221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명체납액구간체납건수체납금액누적체납건수누적체납금액
세목명1.0000.0000.4710.4110.5710.372
체납액구간0.0001.0000.0000.7160.0000.683
체납건수0.4710.0001.0000.6440.9940.669
체납금액0.4110.7160.6441.0000.7030.973
누적체납건수0.5710.0000.9940.7031.0000.736
누적체납금액0.3720.6830.6690.9730.7361.000
2023-12-12T22:16:28.228213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납액구간세목명
체납액구간1.0000.000
세목명0.0001.000
2023-12-12T22:16:28.338259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납건수체납금액누적체납건수누적체납금액세목명체납액구간
체납건수1.0000.4220.9580.5060.1810.000
체납금액0.4221.0000.2780.9670.2400.397
누적체납건수0.9580.2781.0000.3990.2330.000
누적체납금액0.5060.9670.3991.0000.2170.369
세목명0.1810.2400.2330.2171.0000.000
체납액구간0.0000.3970.0000.3690.0001.000

Missing values

2023-12-12T22:16:25.037652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:16:25.180095image/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
0제주특별자치도제주시501102020재산세5백만원~1천만원미만5035082979050350829790
1제주특별자치도제주시501102020재산세5억원~10억원미만2150271908032139512430
2제주특별자치도제주시501102020재산세5천만원~1억원미만21258556502125855650
3제주특별자치도제주시501102020주민세10만원 미만2035129022117042364587708350
4제주특별자치도제주시501102020주민세10만원~30만원미만831331156018730991810
5제주특별자치도제주시501102020주민세1백만원~3백만원미만697014102132253820
6제주특별자치도제주시501102020주민세30만원~50만원미만1869685603514171640
7제주특별자치도제주시501102020주민세3백만원~5백만원미만311731230726584710
8제주특별자치도제주시501102020주민세50만원~1백만원미만14106151303525713760
9제주특별자치도제주시501102020주민세5백만원~1천만원미만16255970316622810
시도명시군구명자치단체코드과세년도세목명체납액구간체납건수체납금액누적체납건수누적체납금액
42제주특별자치도제주시501102020자동차세50만원~1백만원미만635704602011566730
43제주특별자치도제주시501102020재산세10만원 미만1050931407336023689700616600
44제주특별자치도제주시501102020재산세10만원~30만원미만6117107570067085241465406190
45제주특별자치도제주시501102020재산세1백만원~3백만원미만257428127700316519099480
46제주특별자치도제주시501102020재산세1천만원~3천만원미만3654356742037560206600
47제주특별자치도제주시501102020재산세30만원~50만원미만8023062907401070409215120
48제주특별자치도제주시501102020재산세3백만원~5백만원미만5118531758054196126360
49제주특별자치도제주시501102020재산세3억원~5억원미만14436280301443628030
50제주특별자치도제주시501102020재산세3천만원~5천만원미만265721430265721430
51제주특별자치도제주시501102020재산세50만원~1백만원미만515350855300733495993530