Overview

Dataset statistics

Number of variables9
Number of observations105
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory77.3 B

Variable types

Numeric2
Categorical6
Boolean1

Dataset

Description경상북도 문경시 세목별 납세자 현황을 제공하며, 2019년부터 2021년까지 세목명, 납세자유형, 납세자수 등을 제공합니다.
Author경상북도 문경시
URLhttps://www.data.go.kr/data/15078714/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
연번 is highly overall correlated with 과세년도High correlation
과세년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:23:46.113101
Analysis finished2023-12-12 13:23:46.991491
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T22:23:47.082357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q127
median53
Q379
95-th percentile99.8
Maximum105
Range104
Interquartile range (IQR)52

Descriptive statistics

Standard deviation30.454885
Coefficient of variation (CV)0.57462047
Kurtosis-1.2
Mean53
Median Absolute Deviation (MAD)26
Skewness0
Sum5565
Variance927.5
MonotonicityStrictly increasing
2023-12-12T22:23:47.257531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
80 1
 
1.0%
78 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
Other values (95) 95
90.5%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
105 1
1.0%
104 1
1.0%
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
경상북도
105 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 105
100.0%

Length

2023-12-12T22:23:47.395887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:47.523052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 105
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
문경시
105 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문경시 105
100.0%

Length

2023-12-12T22:23:47.632277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:47.747329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문경시 105
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
47280
105 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47280
2nd row47280
3rd row47280
4th row47280
5th row47280

Common Values

ValueCountFrequency (%)
47280 105
100.0%

Length

2023-12-12T22:23:47.919257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:48.020702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47280 105
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size972.0 B
2020
36 
2019
35 
2021
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2020 36
34.3%
2019 35
33.3%
2021 34
32.4%

Length

2023-12-12T22:23:48.130803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:48.242744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 36
34.3%
2019 35
33.3%
2021 34
32.4%

세목명
Categorical

Distinct10
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size972.0 B
재산세
12 
주민세
12 
취득세
12 
자동차세
12 
등록면허세
12 
Other values (5)
45 

Length

Max length7
Median length5
Mean length4.2190476
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재산세 12
11.4%
주민세 12
11.4%
취득세 12
11.4%
자동차세 12
11.4%
등록면허세 12
11.4%
지방소득세 12
11.4%
지역자원시설세 12
11.4%
등록세 11
10.5%
담배소비세 8
7.6%
지방소비세 2
 
1.9%

Length

2023-12-12T22:23:48.371910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:48.533616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 12
11.4%
주민세 12
11.4%
취득세 12
11.4%
자동차세 12
11.4%
등록면허세 12
11.4%
지방소득세 12
11.4%
지역자원시설세 12
11.4%
등록세 11
10.5%
담배소비세 8
7.6%
지방소비세 2
 
1.9%

납세자유형
Categorical

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size972.0 B
법인
54 
개인
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row법인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
법인 54
51.4%
개인 51
48.6%

Length

2023-12-12T22:23:48.724280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:23:48.823689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 54
51.4%
개인 51
48.6%

관내_관외
Boolean

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size237.0 B
False
53 
True
52 
ValueCountFrequency (%)
False 53
50.5%
True 52
49.5%
2023-12-12T22:23:48.910457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

납세자수
Real number (ℝ)

Distinct94
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4675.8286
Minimum1
Maximum34712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T22:23:49.018225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2
Q134
median635
Q32160
95-th percentile31141.4
Maximum34712
Range34711
Interquartile range (IQR)2126

Descriptive statistics

Standard deviation9576.774
Coefficient of variation (CV)2.0481448
Kurtosis3.8835172
Mean4675.8286
Median Absolute Deviation (MAD)626
Skewness2.3011678
Sum490962
Variance91714601
MonotonicityNot monotonic
2023-12-12T22:23:49.175781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
5.7%
2 3
 
2.9%
4 3
 
2.9%
5 2
 
1.9%
3 2
 
1.9%
153 1
 
1.0%
20 1
 
1.0%
483 1
 
1.0%
34712 1
 
1.0%
31043 1
 
1.0%
Other values (84) 84
80.0%
ValueCountFrequency (%)
1 6
5.7%
2 3
2.9%
3 2
 
1.9%
4 3
2.9%
5 2
 
1.9%
9 1
 
1.0%
11 1
 
1.0%
13 1
 
1.0%
14 1
 
1.0%
15 1
 
1.0%
ValueCountFrequency (%)
34712 1
1.0%
34263 1
1.0%
33981 1
1.0%
32530 1
1.0%
31838 1
1.0%
31166 1
1.0%
31043 1
1.0%
30919 1
1.0%
30589 1
1.0%
24302 1
1.0%

Interactions

2023-12-12T22:23:46.577144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:23:46.405294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:23:46.659946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:23:46.482355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:23:49.282093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번과세년도세목명납세자유형관내_관외납세자수
연번1.0000.9490.8070.0000.0000.000
과세년도0.9491.0000.0000.0000.0000.000
세목명0.8070.0001.0000.0000.0000.431
납세자유형0.0000.0000.0001.0000.0000.438
관내_관외0.0000.0000.0000.0001.0000.364
납세자수0.0000.0000.4310.4380.3641.000
2023-12-12T22:23:49.413530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도납세자유형관내_관외세목명
과세년도1.0000.0000.0000.000
납세자유형0.0001.0000.0000.000
관내_관외0.0000.0001.0000.000
세목명0.0000.0000.0001.000
2023-12-12T22:23:49.522662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번납세자수과세년도세목명납세자유형관내_관외
연번1.000-0.0480.9080.3710.0000.000
납세자수-0.0481.0000.0000.2300.4570.380
과세년도0.9080.0001.0000.0000.0000.000
세목명0.3710.2300.0001.0000.0000.000
납세자유형0.0000.4570.0000.0001.0000.000
관내_관외0.0000.3800.0000.0000.0001.000

Missing values

2023-12-12T22:23:46.790479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:23:46.939824image/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

연번시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
01경상북도문경시472802019등록세개인N153
12경상북도문경시472802019등록세개인Y176
23경상북도문경시472802019등록세법인N2
34경상북도문경시472802019등록세법인Y13
45경상북도문경시472802019재산세개인N30589
56경상북도문경시472802019재산세개인Y33981
67경상북도문경시472802019재산세법인N459
78경상북도문경시472802019재산세법인Y1631
89경상북도문경시472802019주민세개인N2193
910경상북도문경시472802019주민세개인Y32530
연번시도명시군구명자치단체코드과세년도세목명납세자유형관내_관외납세자수
9596경상북도문경시472802021등록면허세법인Y1006
9697경상북도문경시472802021지방소득세개인N1255
9798경상북도문경시472802021지방소득세개인Y9850
9899경상북도문경시472802021지방소득세법인N290
99100경상북도문경시472802021지방소득세법인Y898
100101경상북도문경시472802021지방소비세법인Y1
101102경상북도문경시472802021지역자원시설세개인N3
102103경상북도문경시472802021지역자원시설세개인Y21
103104경상북도문경시472802021지역자원시설세법인N2
104105경상북도문경시472802021지역자원시설세법인Y14