Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory70.9 B

Variable types

Categorical5
Text1
Numeric2

Dataset

Description지방세 과세를 위해 세원이 되는 과세 대상 유형별 부과된 현황으로 과세연도, 세목명, 세원유형명, 부과건수, 부과금액으로 구성되어있음
Author경상남도 함양군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15079204

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
부과건수 is highly overall correlated with 부과금액High correlation
부과금액 is highly overall correlated with 부과건수 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 부과금액High correlation
세원 유형명 has unique valuesUnique
부과건수 has 10 (21.7%) zerosZeros
부과금액 has 10 (21.7%) zerosZeros

Reproduction

Analysis started2024-04-06 08:02:43.378440
Analysis finished2024-04-06 08:02:45.255504
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
경상남도
46 

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 46
100.0%

Length

2024-04-06T17:02:45.412616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:02:45.649109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 46
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
함양군
46 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양군 46
100.0%

Length

2024-04-06T17:02:45.861287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:02:46.050198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함양군 46
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
48870
46 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48870
2nd row48870
3rd row48870
4th row48870
5th row48870

Common Values

ValueCountFrequency (%)
48870 46
100.0%

Length

2024-04-06T17:02:46.246144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:02:46.465333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48870 46
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2022
46 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 46
100.0%

Length

2024-04-06T17:02:46.672437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:02:46.884958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 46
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
취득세
9 
자동차세
7 
주민세
7 
재산세
5 
레저세
4 
Other values (8)
14 

Length

Max length7
Median length3
Mean length3.7826087
Min length2

Unique

Unique5 ?
Unique (%)10.9%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row취득세
5th row취득세

Common Values

ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

Length

2024-04-06T17:02:47.085911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취득세 9
19.6%
자동차세 7
15.2%
주민세 7
15.2%
재산세 5
10.9%
레저세 4
8.7%
지방소득세 4
8.7%
지역자원시설세 3
 
6.5%
등록면허세 2
 
4.3%
담배소비세 1
 
2.2%
교육세 1
 
2.2%
Other values (3) 3
 
6.5%

세원 유형명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-06T17:02:47.496207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.0217391
Min length2

Characters and Unicode

Total characters277
Distinct characters73
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row담배소비세
2nd row교육세
3rd row도시계획세
4th row건축물
5th row주택(개별)
ValueCountFrequency (%)
담배소비세 1
 
2.2%
주민세(양도소득 1
 
2.2%
지방소득세(종합소득 1
 
2.2%
승합 1
 
2.2%
기타승용 1
 
2.2%
승용 1
 
2.2%
주민세(사업소분 1
 
2.2%
주민세(개인분 1
 
2.2%
주민세(종업원분 1
 
2.2%
주민세(특별징수 1
 
2.2%
Other values (36) 36
78.3%
2024-04-06T17:02:48.170039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 27
 
9.7%
) 24
 
8.7%
( 24
 
8.7%
소 14
 
5.1%
주 11
 
4.0%
지 10
 
3.6%
득 9
 
3.2%
민 7
 
2.5%
방 6
 
2.2%
기 5
 
1.8%
Other values (63) 140
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
82.3%
Close Punctuation 24
 
8.7%
Open Punctuation 24
 
8.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
시 5
 
2.2%
산 5
 
2.2%
Other values (60) 129
56.6%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 228
82.3%
Common 49
 
17.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
시 5
 
2.2%
산 5
 
2.2%
Other values (60) 129
56.6%
Common
ValueCountFrequency (%)
) 24
49.0%
( 24
49.0%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 228
82.3%
ASCII 49
 
17.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 27
 
11.8%
소 14
 
6.1%
주 11
 
4.8%
지 10
 
4.4%
득 9
 
3.9%
민 7
 
3.1%
방 6
 
2.6%
기 5
 
2.2%
시 5
 
2.2%
산 5
 
2.2%
Other values (60) 129
56.6%
ASCII
ValueCountFrequency (%)
) 24
49.0%
( 24
49.0%
3 1
 
2.0%

부과건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6693.8478
Minimum0
Maximum112531
Zeros10
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T17:02:48.444090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.75
median151.5
Q35291.5
95-th percentile20894.5
Maximum112531
Range112531
Interquartile range (IQR)5284.75

Descriptive statistics

Standard deviation18451.567
Coefficient of variation (CV)2.7564963
Kurtosis25.30806
Mean6693.8478
Median Absolute Deviation (MAD)151.5
Skewness4.7475577
Sum307917
Variance3.4046032 × 108
MonotonicityNot monotonic
2024-04-06T17:02:48.688421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 10
 
21.7%
635 1
 
2.2%
8074 1
 
2.2%
142 1
 
2.2%
20910 1
 
2.2%
2079 1
 
2.2%
18461 1
 
2.2%
137 1
 
2.2%
9 1
 
2.2%
8423 1
 
2.2%
Other values (27) 27
58.7%
ValueCountFrequency (%)
0 10
21.7%
2 1
 
2.2%
6 1
 
2.2%
9 1
 
2.2%
11 1
 
2.2%
12 1
 
2.2%
22 1
 
2.2%
34 1
 
2.2%
123 1
 
2.2%
128 1
 
2.2%
ValueCountFrequency (%)
112531 1
2.2%
52858 1
2.2%
20910 1
2.2%
20848 1
2.2%
18461 1
2.2%
16257 1
2.2%
11820 1
2.2%
8423 1
2.2%
8074 1
2.2%
7186 1
2.2%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1504244 × 109
Minimum0
Maximum1.5907504 × 1010
Zeros10
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T17:02:48.948906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1712250
median1.89916 × 108
Q31.4345332 × 109
95-th percentile3.7467928 × 109
Maximum1.5907504 × 1010
Range1.5907504 × 1010
Interquartile range (IQR)1.433821 × 109

Descriptive statistics

Standard deviation2.508011 × 109
Coefficient of variation (CV)2.1800746
Kurtosis27.365332
Mean1.1504244 × 109
Median Absolute Deviation (MAD)1.89916 × 108
Skewness4.7874916
Sum5.2919521 × 1010
Variance6.2901191 × 1018
MonotonicityNot monotonic
2024-04-06T17:02:49.191230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 10
 
21.7%
2632181000 1
 
2.2%
618677000 1
 
2.2%
9639000 1
 
2.2%
2815321000 1
 
2.2%
214133000 1
 
2.2%
183959000 1
 
2.2%
177948000 1
 
2.2%
15907504000 1
 
2.2%
128631000 1
 
2.2%
Other values (27) 27
58.7%
ValueCountFrequency (%)
0 10
21.7%
72000 1
 
2.2%
245000 1
 
2.2%
2114000 1
 
2.2%
5958000 1
 
2.2%
6203000 1
 
2.2%
8211000 1
 
2.2%
9639000 1
 
2.2%
15640000 1
 
2.2%
34092000 1
 
2.2%
ValueCountFrequency (%)
15907504000 1
2.2%
4056770000 1
2.2%
3856280000 1
2.2%
3418331000 1
2.2%
2815321000 1
2.2%
2784638000 1
2.2%
2670133000 1
2.2%
2632181000 1
2.2%
1955841000 1
2.2%
1800601000 1
2.2%

Interactions

2024-04-06T17:02:44.135573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:02:43.772781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:02:44.296067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:02:43.946523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:02:49.386459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명세원 유형명부과건수부과금액
세목명1.0001.0000.7560.875
세원 유형명1.0001.0001.0001.000
부과건수0.7561.0001.0000.683
부과금액0.8751.0000.6831.000
2024-04-06T17:02:49.550640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과건수부과금액세목명
부과건수1.0000.7610.490
부과금액0.7611.0000.646
세목명0.4900.6461.000

Missing values

2024-04-06T17:02:44.549111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:02:45.150618image/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

시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
0경상남도함양군488702022담배소비세담배소비세6352632181000
1경상남도함양군488702022교육세교육세1125313418331000
2경상남도함양군488702022도시계획세도시계획세00
3경상남도함양군488702022취득세건축물5001772740000
4경상남도함양군488702022취득세주택(개별)10891220169000
5경상남도함양군488702022취득세주택(단독)147246986000
6경상남도함양군488702022취득세기타22771400000
7경상남도함양군488702022취득세항공기00
8경상남도함양군488702022취득세기계장비128129966000
9경상남도함양군488702022취득세차량27162670133000
시도명시군구명자치단체코드과세년도세목명세원 유형명부과건수부과금액
36경상남도함양군488702022등록면허세등록면허세(면허)8423128631000
37경상남도함양군488702022등록면허세등록면허세(등록)8074618677000
38경상남도함양군488702022지역자원시설세지역자원시설세(소방)11820582878000
39경상남도함양군488702022지역자원시설세지역자원시설세(시설)00
40경상남도함양군488702022지역자원시설세지역자원시설세(특자)1238211000
41경상남도함양군488702022지방소득세지방소득세(특별징수)54051800601000
42경상남도함양군488702022지방소득세지방소득세(법인소득)6851955841000
43경상남도함양군488702022지방소득세지방소득세(양도소득)632595356000
44경상남도함양군488702022지방소득세지방소득세(종합소득)4705853073000
45경상남도함양군488702022체납체납208483856280000