Overview

Dataset statistics

Number of variables10
Number of observations35
Missing cells3
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory89.8 B

Variable types

Categorical6
Numeric4

Dataset

Description인천광역시 남동구 지방세 비과/감면율 현황에 대한 데이터로(세목명, 과세년도, 비과세금액, 감면금액, 부과금액, 비과세감면율, 데이터기준일) 등을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15079464&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 1 other fieldsHigh correlation
세목명 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세금액 has 3 (8.6%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 2 (5.7%) zerosZeros
부과금액 has 3 (8.6%) zerosZeros
비과세감면율 has 4 (11.4%) zerosZeros

Reproduction

Analysis started2024-03-18 02:02:19.826791
Analysis finished2024-03-18 02:02:22.829376
Duration3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
인천광역시
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 35
100.0%

Length

2024-03-18T11:02:22.888810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:22.965860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 35
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
남동구
35 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 35
100.0%

Length

2024-03-18T11:02:23.044447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:23.128978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 35
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
28200
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28200
2nd row28200
3rd row28200
4th row28200
5th row28200

Common Values

ValueCountFrequency (%)
28200 35
100.0%

Length

2024-03-18T11:02:23.242489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:23.353379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28200 35
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
재산세
5 
주민세
5 
취득세
5 
자동차세
5 
등록면허세
5 
Other values (3)
10 

Length

Max length7
Median length3
Mean length4
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row등록세
2nd row재산세
3rd row주민세
4th row취득세
5th row자동차세

Common Values

ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
취득세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
등록세 4
11.4%
교육세 1
 
2.9%

Length

2024-03-18T11:02:23.454818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:23.561826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재산세 5
14.3%
주민세 5
14.3%
취득세 5
14.3%
자동차세 5
14.3%
등록면허세 5
14.3%
지역자원시설세 5
14.3%
등록세 4
11.4%
교육세 1
 
2.9%

과세년도
Categorical

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2019
8 
2017
7 
2018
7 
2020
7 
2021
6 

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 (%)
2019 8
22.9%
2017 7
20.0%
2018 7
20.0%
2020 7
20.0%
2021 6
17.1%

Length

2024-03-18T11:02:23.665418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:23.760606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 8
22.9%
2017 7
20.0%
2018 7
20.0%
2020 7
20.0%
2021 6
17.1%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct31
Distinct (%)96.9%
Missing3
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean6.8287088 × 109
Minimum0
Maximum3.8654979 × 1010
Zeros2
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-18T11:02:23.863820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7342500
Q11.4852925 × 108
median5.37481 × 108
Q34.291073 × 109
95-th percentile3.6428024 × 1010
Maximum3.8654979 × 1010
Range3.8654979 × 1010
Interquartile range (IQR)4.1425438 × 109

Descriptive statistics

Standard deviation1.2806932 × 1010
Coefficient of variation (CV)1.8754544
Kurtosis1.7059333
Mean6.8287088 × 109
Median Absolute Deviation (MAD)4.22061 × 108
Skewness1.8193843
Sum2.1851868 × 1011
Variance1.640175 × 1020
MonotonicityNot monotonic
2024-03-18T11:02:23.982458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 2
 
5.7%
158419000 1
 
2.9%
666976000 1
 
2.9%
41516000 1
 
2.9%
166007000 1
 
2.9%
3709521000 1
 
2.9%
19643000 1
 
2.9%
31881818000 1
 
2.9%
644501000 1
 
2.9%
156319000 1
 
2.9%
Other values (21) 21
60.0%
(Missing) 3
 
8.6%
ValueCountFrequency (%)
0 2
5.7%
13350000 1
2.9%
19643000 1
2.9%
41516000 1
2.9%
112925000 1
2.9%
117915000 1
2.9%
144975000 1
2.9%
149714000 1
2.9%
153849000 1
2.9%
156319000 1
2.9%
ValueCountFrequency (%)
38654979000 1
2.9%
37330258000 1
2.9%
35689832000 1
2.9%
32373185000 1
2.9%
31881818000 1
2.9%
13635941000 1
2.9%
10046072000 1
2.9%
5746379000 1
2.9%
3805971000 1
2.9%
3709521000 1
2.9%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0534201 × 109
Minimum1000
Maximum3.4963432 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-18T11:02:24.095582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile38738100
Q12.322395 × 108
median7.86175 × 108
Q37.65663 × 109
95-th percentile2.9572067 × 1010
Maximum3.4963432 × 1010
Range3.4963431 × 1010
Interquartile range (IQR)7.4243905 × 109

Descriptive statistics

Standard deviation1.0257106 × 1010
Coefficient of variation (CV)1.6944316
Kurtosis2.2897164
Mean6.0534201 × 109
Median Absolute Deviation (MAD)7.48573 × 108
Skewness1.9016258
Sum2.118697 × 1011
Variance1.0520823 × 1020
MonotonicityNot monotonic
2024-03-18T11:02:24.202470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
47283000 1
 
2.9%
7412117000 1
 
2.9%
1466956000 1
 
2.9%
245242000 1
 
2.9%
39225000 1
 
2.9%
7895903000 1
 
2.9%
231324000 1
 
2.9%
28959834000 1
 
2.9%
2090677000 1
 
2.9%
7549288000 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1000 1
2.9%
37602000 1
2.9%
39225000 1
2.9%
47283000 1
2.9%
54278000 1
2.9%
78784000 1
2.9%
96992000 1
2.9%
222936000 1
2.9%
231324000 1
2.9%
233155000 1
2.9%
ValueCountFrequency (%)
34963432000 1
2.9%
31000612000 1
2.9%
28959834000 1
2.9%
27224960000 1
2.9%
26462706000 1
2.9%
8548674000 1
2.9%
7986834000 1
2.9%
7895903000 1
2.9%
7763972000 1
2.9%
7549288000 1
2.9%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1777012 × 1010
Minimum0
Maximum3.2691 × 1011
Zeros3
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-18T11:02:24.445235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5645414 × 1010
median1.8609871 × 1010
Q39.5244372 × 1010
95-th percentile2.780542 × 1011
Maximum3.2691 × 1011
Range3.2691 × 1011
Interquartile range (IQR)7.9598957 × 1010

Descriptive statistics

Standard deviation9.3765368 × 1010
Coefficient of variation (CV)1.3063426
Kurtosis1.8233808
Mean7.1777012 × 1010
Median Absolute Deviation (MAD)1.8609871 × 1010
Skewness1.7227126
Sum2.5121954 × 1012
Variance8.7919443 × 1021
MonotonicityNot monotonic
2024-03-18T11:02:24.551581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 3
 
8.6%
16911436000 1
 
2.9%
15336788000 1
 
2.9%
65645000 1
 
2.9%
107279000000 1
 
2.9%
17903720000 1
 
2.9%
304013000000 1
 
2.9%
63046303000 1
 
2.9%
15674354000 1
 
2.9%
92480625000 1
 
2.9%
Other values (23) 23
65.7%
ValueCountFrequency (%)
0 3
8.6%
65645000 1
 
2.9%
14869667000 1
 
2.9%
15162670000 1
 
2.9%
15336788000 1
 
2.9%
15362471000 1
 
2.9%
15626804000 1
 
2.9%
15664025000 1
 
2.9%
15674354000 1
 
2.9%
15906060000 1
 
2.9%
ValueCountFrequency (%)
326910000000 1
2.9%
304013000000 1
2.9%
266929000000 1
2.9%
265875000000 1
2.9%
248772000000 1
2.9%
109980000000 1
2.9%
107279000000 1
2.9%
102316000000 1
2.9%
98008118000 1
2.9%
92480625000 1
2.9%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.291143
Minimum0
Maximum59.75
Zeros4
Zeros (%)11.4%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-18T11:02:24.657978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.985
median5.72
Q314.8
95-th percentile44.706
Maximum59.75
Range59.75
Interquartile range (IQR)12.815

Descriptive statistics

Standard deviation17.04262
Coefficient of variation (CV)1.2822539
Kurtosis0.79565417
Mean13.291143
Median Absolute Deviation (MAD)4.51
Skewness1.471849
Sum465.19
Variance290.45088
MonotonicityNot monotonic
2024-03-18T11:02:24.761988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 4
 
11.4%
1.37 2
 
5.7%
43.02 1
 
2.9%
5.89 1
 
2.9%
0.77 1
 
2.9%
3.49 1
 
2.9%
9.46 1
 
2.9%
36.76 1
 
2.9%
5.81 1
 
2.9%
45.56 1
 
2.9%
Other values (21) 21
60.0%
ValueCountFrequency (%)
0.0 4
11.4%
0.77 1
 
2.9%
1.21 1
 
2.9%
1.37 2
5.7%
1.94 1
 
2.9%
2.03 1
 
2.9%
3.49 1
 
2.9%
3.58 1
 
2.9%
3.8 1
 
2.9%
3.82 1
 
2.9%
ValueCountFrequency (%)
59.75 1
2.9%
45.56 1
2.9%
44.34 1
2.9%
44.29 1
2.9%
43.39 1
2.9%
43.02 1
2.9%
36.76 1
2.9%
16.5 1
2.9%
15.02 1
2.9%
14.58 1
2.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-02-17
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-02-17
2nd row2023-02-17
3rd row2023-02-17
4th row2023-02-17
5th row2023-02-17

Common Values

ValueCountFrequency (%)
2023-02-17 35
100.0%

Length

2024-03-18T11:02:24.874500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:02:24.965313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-02-17 35
100.0%

Interactions

2024-03-18T11:02:22.315030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.244667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.735904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.039237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.395154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.378088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.811465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.111822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.466649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.580055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.890615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.180071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.535279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.652273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:21.964960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:02:22.250240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:02:25.017541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.5460.7300.8140.698
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.5460.0001.0000.8060.8500.888
감면금액0.7300.0000.8061.0000.8430.730
부과금액0.8140.0000.8500.8431.0000.778
비과세감면율0.6980.0000.8880.7300.7781.000
2024-03-18T11:02:25.103825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2024-03-18T11:02:25.178957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7960.5940.6750.3170.000
감면금액0.7961.0000.8140.7140.5350.000
부과금액0.5940.8141.0000.4490.5980.000
비과세감면율0.6750.7140.4491.0000.4600.000
세목명0.3170.5350.5980.4601.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2024-03-18T11:02:22.640721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:02:22.771912image/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

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율데이터기준일
0인천광역시남동구28200등록세2017<NA>4728300000.02023-02-17
1인천광역시남동구28200재산세20173237318500074121170009248062500043.022023-02-17
2인천광역시남동구28200주민세201711292500096992000173752680001.212023-02-17
3인천광역시남동구28200취득세2017136359410002646270600026692900000015.022023-02-17
4인천광역시남동구28200자동차세20175720160001913132000551213460004.512023-02-17
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