Overview

Dataset statistics

Number of variables19
Number of observations69
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory168.9 B

Variable types

Categorical6
Numeric13

Dataset

Description춘천시 지방세 관련 전반적인 부과, 징수, 과세, 비과세 및 감면에 대한 통합 자료로, 시도명, 시군구명, 자치단체코드, 과세년도, 세목명, 부과금액, 수납급액, 환급금액, 결손금액, 미수납 금액, 징수율, 과세건수, 과세금액, 비과세건수, 비과세감면금액, 비과세금액, 감면금액, 비과세감면율, 데이터기준일에 대한 자료.기존 지방세 징수현황, 지방세 과세현황, 지방세 비과 감면율의 3개 목록을 단일 목록으로 통합
Author강원특별자치도 춘천시
URLhttps://www.data.go.kr/data/15103296/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
부과금액 is highly overall correlated with 수납급액 and 5 other fieldsHigh correlation
수납급액 is highly overall correlated with 부과금액 and 5 other fieldsHigh correlation
환급금액 is highly overall correlated with 부과금액 and 4 other fieldsHigh correlation
결손금액 is highly overall correlated with 부과금액 and 2 other fieldsHigh correlation
미수납금액 is highly overall correlated with 부과금액 and 4 other fieldsHigh correlation
징수율 is highly overall correlated with 수납급액 and 1 other fieldsHigh correlation
과세건수 is highly overall correlated with 부과금액 and 9 other fieldsHigh correlation
과세금액 is highly overall correlated with 부과금액 and 6 other fieldsHigh correlation
비과세건수 is highly overall correlated with 과세건수 and 5 other fieldsHigh correlation
비과세감면금액 is highly overall correlated with 과세건수 and 4 other fieldsHigh correlation
비과세금액 is highly overall correlated with 과세건수 and 5 other fieldsHigh correlation
감면금액 is highly overall correlated with 과세건수 and 5 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 과세건수 and 5 other fieldsHigh correlation
세목명 is highly overall correlated with 과세건수 and 4 other fieldsHigh correlation
부과금액 has 15 (21.7%) zerosZeros
수납급액 has 15 (21.7%) zerosZeros
환급금액 has 20 (29.0%) zerosZeros
결손금액 has 29 (42.0%) zerosZeros
미수납금액 has 24 (34.8%) zerosZeros
징수율 has 15 (21.7%) zerosZeros
과세건수 has 20 (29.0%) zerosZeros
과세금액 has 20 (29.0%) zerosZeros
비과세건수 has 31 (44.9%) zerosZeros
비과세감면금액 has 31 (44.9%) zerosZeros
비과세금액 has 39 (56.5%) zerosZeros
감면금액 has 31 (44.9%) zerosZeros
비과세감면율 has 38 (55.1%) zerosZeros

Reproduction

Analysis started2023-12-12 04:48:33.773552
Analysis finished2023-12-12 04:48:54.646786
Duration20.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
강원특별자치도
69 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원특별자치도 69
100.0%

Length

2023-12-12T13:48:54.716480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:54.846126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원특별자치도 69
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
춘천시
69 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
춘천시 69
100.0%

Length

2023-12-12T13:48:54.956905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:55.064666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천시 69
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
51110
69 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row51110
2nd row51110
3rd row51110
4th row51110
5th row51110

Common Values

ValueCountFrequency (%)
51110 69
100.0%

Length

2023-12-12T13:48:55.176671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:55.299570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
51110 69
100.0%

과세년도
Categorical

Distinct5
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size684.0 B
2018
15 
2019
14 
2020
14 
2021
13 
2022
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 15
21.7%
2019 14
20.3%
2020 14
20.3%
2021 13
18.8%
2022 13
18.8%

Length

2023-12-12T13:48:55.426079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:48:55.588570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 15
21.7%
2019 14
20.3%
2020 14
20.3%
2021 13
18.8%
2022 13
18.8%

세목명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size684.0 B
레저세
재산세
주민세
취득세
자동차세
Other values (10)
44 

Length

Max length7
Median length5
Mean length4.3768116
Min length3

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row도축세
2nd row레저세
3rd row재산세
4th row주민세
5th row취득세

Common Values

ValueCountFrequency (%)
레저세 5
 
7.2%
재산세 5
 
7.2%
주민세 5
 
7.2%
취득세 5
 
7.2%
자동차세 5
 
7.2%
과년도수입 5
 
7.2%
담배소비세 5
 
7.2%
도시계획세 5
 
7.2%
등록면허세 5
 
7.2%
지방교육세 5
 
7.2%
Other values (5) 19
27.5%

Length

2023-12-12T13:48:55.747041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레저세 5
 
7.2%
재산세 5
 
7.2%
주민세 5
 
7.2%
취득세 5
 
7.2%
자동차세 5
 
7.2%
과년도수입 5
 
7.2%
담배소비세 5
 
7.2%
도시계획세 5
 
7.2%
등록면허세 5
 
7.2%
지방교육세 5
 
7.2%
Other values (5) 19
27.5%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7106705 × 1010
Minimum0
Maximum1.44081 × 1011
Zeros15
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:55.903075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.824361 × 109
median1.2437727 × 1010
Q34.4892983 × 1010
95-th percentile1.0086522 × 1011
Maximum1.44081 × 1011
Range1.44081 × 1011
Interquartile range (IQR)3.9068622 × 1010

Descriptive statistics

Standard deviation3.3082524 × 1010
Coefficient of variation (CV)1.2204554
Kurtosis2.617965
Mean2.7106705 × 1010
Median Absolute Deviation (MAD)1.2437727 × 1010
Skewness1.677622
Sum1.8703626 × 1012
Variance1.0944534 × 1021
MonotonicityNot monotonic
2023-12-12T13:48:56.100736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
21.7%
44892983000 1
 
1.4%
7752000000 1
 
1.4%
7921053000 1
 
1.4%
12437727000 1
 
1.4%
19430106000 1
 
1.4%
8518382000 1
 
1.4%
48540113000 1
 
1.4%
52241844000 1
 
1.4%
6249778000 1
 
1.4%
Other values (45) 45
65.2%
ValueCountFrequency (%)
0 15
21.7%
153874000 1
 
1.4%
5712509000 1
 
1.4%
5824361000 1
 
1.4%
5841858000 1
 
1.4%
6101778000 1
 
1.4%
6249778000 1
 
1.4%
6319197000 1
 
1.4%
7006309000 1
 
1.4%
7367265000 1
 
1.4%
ValueCountFrequency (%)
144081000000 1
1.4%
126472000000 1
1.4%
113270000000 1
1.4%
105904000000 1
1.4%
93307049000 1
1.4%
83316107000 1
1.4%
73683219000 1
1.4%
59852333000 1
1.4%
57178225000 1
1.4%
55881600000 1
1.4%

수납급액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5692884 × 1010
Minimum0
Maximum1.43694 × 1011
Zeros15
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:56.274463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.361535 × 109
median8.49877 × 109
Q34.3675618 × 1010
95-th percentile9.7591972 × 1010
Maximum1.43694 × 1011
Range1.43694 × 1011
Interquartile range (IQR)4.2314083 × 1010

Descriptive statistics

Standard deviation3.2861945 × 1010
Coefficient of variation (CV)1.2790291
Kurtosis2.8424792
Mean2.5692884 × 1010
Median Absolute Deviation (MAD)8.49877 × 109
Skewness1.7356101
Sum1.772809 × 1012
Variance1.0799074 × 1021
MonotonicityNot monotonic
2023-12-12T13:48:56.431265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
21.7%
43675618000 1
 
1.4%
7752000000 1
 
1.4%
7739940000 1
 
1.4%
2859782000 1
 
1.4%
19430106000 1
 
1.4%
8498770000 1
 
1.4%
45828856000 1
 
1.4%
51154322000 1
 
1.4%
6090874000 1
 
1.4%
Other values (45) 45
65.2%
ValueCountFrequency (%)
0 15
21.7%
153874000 1
 
1.4%
1351103000 1
 
1.4%
1361535000 1
 
1.4%
2859782000 1
 
1.4%
5480940000 1
 
1.4%
5798263000 1
 
1.4%
5814561000 1
 
1.4%
5862940000 1
 
1.4%
6090874000 1
 
1.4%
ValueCountFrequency (%)
143694000000 1
1.4%
126239000000 1
1.4%
112423000000 1
1.4%
100594000000 1
1.4%
93088929000 1
1.4%
81200749000 1
1.4%
72183930000 1
1.4%
58422264000 1
1.4%
55900571000 1
1.4%
53931102000 1
1.4%

환급금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9356006 × 108
Minimum0
Maximum5.432514 × 109
Zeros20
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:56.597439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median22632000
Q33.13491 × 108
95-th percentile2.5982776 × 109
Maximum5.432514 × 109
Range5.432514 × 109
Interquartile range (IQR)3.13491 × 108

Descriptive statistics

Standard deviation1.0956605 × 109
Coefficient of variation (CV)2.2199132
Kurtosis9.0260728
Mean4.9356006 × 108
Median Absolute Deviation (MAD)22632000
Skewness2.9703138
Sum3.4055644 × 1010
Variance1.2004719 × 1018
MonotonicityNot monotonic
2023-12-12T13:48:56.768189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
29.0%
83084000 1
 
1.4%
2006865000 1
 
1.4%
5321000 1
 
1.4%
3965439000 1
 
1.4%
2853000 1
 
1.4%
37224000 1
 
1.4%
357147000 1
 
1.4%
391019000 1
 
1.4%
1719000 1
 
1.4%
Other values (40) 40
58.0%
ValueCountFrequency (%)
0 20
29.0%
18000 1
 
1.4%
40000 1
 
1.4%
1719000 1
 
1.4%
1798000 1
 
1.4%
2033000 1
 
1.4%
2853000 1
 
1.4%
3421000 1
 
1.4%
4004000 1
 
1.4%
5321000 1
 
1.4%
ValueCountFrequency (%)
5432514000 1
1.4%
4626246000 1
1.4%
3965439000 1
1.4%
2885172000 1
1.4%
2167936000 1
1.4%
2058458000 1
1.4%
2006865000 1
1.4%
1814308000 1
1.4%
1488771000 1
1.4%
1430794000 1
1.4%

결손금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7368732 × 108
Minimum0
Maximum3.417949 × 109
Zeros29
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:56.919834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median86000
Q35489000
95-th percentile1.2113324 × 109
Maximum3.417949 × 109
Range3.417949 × 109
Interquartile range (IQR)5489000

Descriptive statistics

Standard deviation6.0178788 × 108
Coefficient of variation (CV)3.4647773
Kurtosis16.918061
Mean1.7368732 × 108
Median Absolute Deviation (MAD)86000
Skewness4.0661223
Sum1.1984425 × 1010
Variance3.6214865 × 1017
MonotonicityNot monotonic
2023-12-12T13:48:57.070134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 29
42.0%
659000 1
 
1.4%
170000 1
 
1.4%
2927000 1
 
1.4%
118179000 1
 
1.4%
31000 1
 
1.4%
1175777000 1
 
1.4%
136000 1
 
1.4%
28943000 1
 
1.4%
6221000 1
 
1.4%
Other values (31) 31
44.9%
ValueCountFrequency (%)
0 29
42.0%
5000 1
 
1.4%
9000 1
 
1.4%
20000 1
 
1.4%
22000 1
 
1.4%
31000 1
 
1.4%
86000 1
 
1.4%
97000 1
 
1.4%
131000 1
 
1.4%
136000 1
 
1.4%
ValueCountFrequency (%)
3417949000 1
1.4%
2564166000 1
1.4%
2232153000 1
1.4%
1235036000 1
1.4%
1175777000 1
1.4%
557754000 1
1.4%
479065000 1
1.4%
118179000 1
1.4%
51311000 1
1.4%
28943000 1
1.4%

미수납금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct46
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2401269 × 109
Minimum0
Maximum1.0477843 × 1010
Zeros24
Zeros (%)34.8%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:57.237173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.58916 × 108
Q31.31189 × 109
95-th percentile7.789186 × 109
Maximum1.0477843 × 1010
Range1.0477843 × 1010
Interquartile range (IQR)1.31189 × 109

Descriptive statistics

Standard deviation2.318004 × 109
Coefficient of variation (CV)1.8691667
Kurtosis6.2633852
Mean1.2401269 × 109
Median Absolute Deviation (MAD)1.58916 × 108
Skewness2.5881855
Sum8.5568758 × 1010
Variance5.3731425 × 1018
MonotonicityNot monotonic
2023-12-12T13:48:57.417708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 24
34.8%
119171000 1
 
1.4%
1311890000 1
 
1.4%
181082000 1
 
1.4%
8402168000 1
 
1.4%
19476000 1
 
1.4%
2682314000 1
 
1.4%
1081301000 1
 
1.4%
158245000 1
 
1.4%
952893000 1
 
1.4%
Other values (36) 36
52.2%
ValueCountFrequency (%)
0 24
34.8%
16417000 1
 
1.4%
17514000 1
 
1.4%
19476000 1
 
1.4%
25518000 1
 
1.4%
27166000 1
 
1.4%
119171000 1
 
1.4%
141850000 1
 
1.4%
152519000 1
 
1.4%
156079000 1
 
1.4%
ValueCountFrequency (%)
10477843000 1
1.4%
8642093000 1
1.4%
8402168000 1
1.4%
8168248000 1
1.4%
7220593000 1
1.4%
5310049000 1
1.4%
3146543000 1
1.4%
3067317000 1
1.4%
2754975000 1
1.4%
2732603000 1
1.4%

징수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.507246
Minimum0
Maximum100
Zeros15
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:57.625342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123
median97
Q399
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)76

Descriptive statistics

Standard deviation42.290182
Coefficient of variation (CV)0.59141114
Kurtosis-0.87960536
Mean71.507246
Median Absolute Deviation (MAD)3
Skewness-1.0335375
Sum4934
Variance1788.4595
MonotonicityNot monotonic
2023-12-12T13:48:57.774254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
100 17
24.6%
0 15
21.7%
98 11
15.9%
97 9
13.0%
96 4
 
5.8%
94 4
 
5.8%
95 2
 
2.9%
45 1
 
1.4%
10 1
 
1.4%
99 1
 
1.4%
Other values (4) 4
 
5.8%
ValueCountFrequency (%)
0 15
21.7%
10 1
 
1.4%
12 1
 
1.4%
23 1
 
1.4%
45 1
 
1.4%
51 1
 
1.4%
93 1
 
1.4%
94 4
 
5.8%
95 2
 
2.9%
96 4
 
5.8%
ValueCountFrequency (%)
100 17
24.6%
99 1
 
1.4%
98 11
15.9%
97 9
13.0%
96 4
 
5.8%
95 2
 
2.9%
94 4
 
5.8%
93 1
 
1.4%
51 1
 
1.4%
45 1
 
1.4%

과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean109047.2
Minimum0
Maximum603510
Zeros20
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:57.912076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median78797
Q3128715
95-th percentile560208.6
Maximum603510
Range603510
Interquartile range (IQR)128715

Descriptive statistics

Standard deviation153517.59
Coefficient of variation (CV)1.4078086
Kurtosis4.1957868
Mean109047.2
Median Absolute Deviation (MAD)78797
Skewness2.0881221
Sum7524257
Variance2.3567652 × 1010
MonotonicityNot monotonic
2023-12-12T13:48:58.088286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
29.0%
46459 1
 
1.4%
126839 1
 
1.4%
486 1
 
1.4%
109875 1
 
1.4%
214345 1
 
1.4%
235696 1
 
1.4%
114323 1
 
1.4%
594645 1
 
1.4%
108826 1
 
1.4%
Other values (40) 40
58.0%
ValueCountFrequency (%)
0 20
29.0%
6 1
 
1.4%
7 1
 
1.4%
9 1
 
1.4%
45 1
 
1.4%
89 1
 
1.4%
102 1
 
1.4%
274 1
 
1.4%
486 1
 
1.4%
655 1
 
1.4%
ValueCountFrequency (%)
603510 1
1.4%
594645 1
1.4%
581646 1
1.4%
562065 1
1.4%
557424 1
1.4%
245944 1
1.4%
235696 1
1.4%
225319 1
1.4%
218160 1
1.4%
217494 1
1.4%

과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)72.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5966571 × 1010
Minimum0
Maximum1.44081 × 1011
Zeros20
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:58.239227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7.942128 × 109
Q34.4892983 × 1010
95-th percentile1.0086522 × 1011
Maximum1.44081 × 1011
Range1.44081 × 1011
Interquartile range (IQR)4.4892983 × 1010

Descriptive statistics

Standard deviation3.3702015 × 1010
Coefficient of variation (CV)1.2979001
Kurtosis2.4680058
Mean2.5966571 × 1010
Median Absolute Deviation (MAD)7.942128 × 109
Skewness1.6564566
Sum1.7916934 × 1012
Variance1.1358258 × 1021
MonotonicityNot monotonic
2023-12-12T13:48:58.433189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20
29.0%
126472000000 1
 
1.4%
7993101000 1
 
1.4%
19430106000 1
 
1.4%
8518382000 1
 
1.4%
48540113000 1
 
1.4%
52241844000 1
 
1.4%
6249778000 1
 
1.4%
32512868000 1
 
1.4%
73683219000 1
 
1.4%
Other values (40) 40
58.0%
ValueCountFrequency (%)
0 20
29.0%
153874000 1
 
1.4%
5712509000 1
 
1.4%
5824361000 1
 
1.4%
5841858000 1
 
1.4%
6101778000 1
 
1.4%
6249778000 1
 
1.4%
6319197000 1
 
1.4%
7006309000 1
 
1.4%
7415889000 1
 
1.4%
ValueCountFrequency (%)
144081000000 1
1.4%
126472000000 1
1.4%
113270000000 1
1.4%
105904000000 1
1.4%
93307049000 1
1.4%
83316107000 1
1.4%
73683219000 1
1.4%
59852333000 1
1.4%
57178225000 1
1.4%
55881600000 1
1.4%

비과세건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9081.8986
Minimum0
Maximum59079
Zeros31
Zeros (%)44.9%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:58.579637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median61
Q311447
95-th percentile50309.2
Maximum59079
Range59079
Interquartile range (IQR)11447

Descriptive statistics

Standard deviation15234.032
Coefficient of variation (CV)1.6774061
Kurtosis3.090161
Mean9081.8986
Median Absolute Deviation (MAD)61
Skewness1.9511627
Sum626651
Variance2.3207573 × 108
MonotonicityNot monotonic
2023-12-12T13:48:58.739190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 31
44.9%
50284 1
 
1.4%
7 1
 
1.4%
95 1
 
1.4%
5114 1
 
1.4%
5985 1
 
1.4%
29459 1
 
1.4%
53054 1
 
1.4%
22307 1
 
1.4%
317 1
 
1.4%
Other values (29) 29
42.0%
ValueCountFrequency (%)
0 31
44.9%
7 1
 
1.4%
12 1
 
1.4%
21 1
 
1.4%
61 1
 
1.4%
70 1
 
1.4%
95 1
 
1.4%
317 1
 
1.4%
372 1
 
1.4%
4136 1
 
1.4%
ValueCountFrequency (%)
59079 1
1.4%
53917 1
1.4%
53054 1
1.4%
50326 1
1.4%
50284 1
1.4%
31185 1
1.4%
29459 1
1.4%
28219 1
1.4%
25131 1
1.4%
24743 1
1.4%

비과세감면금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0288485 × 109
Minimum0
Maximum4.4108189 × 1010
Zeros31
Zeros (%)44.9%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:58.892075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median78000
Q31.21634 × 109
95-th percentile3.4980122 × 1010
Maximum4.4108189 × 1010
Range4.4108189 × 1010
Interquartile range (IQR)1.21634 × 109

Descriptive statistics

Standard deviation1.1224774 × 1010
Coefficient of variation (CV)2.2320763
Kurtosis4.3072171
Mean5.0288485 × 109
Median Absolute Deviation (MAD)78000
Skewness2.3540303
Sum3.4699054 × 1011
Variance1.2599554 × 1020
MonotonicityNot monotonic
2023-12-12T13:48:59.046171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 31
44.9%
5000 2
 
2.9%
1098750000 1
 
1.4%
7000 1
 
1.4%
1103158000 1
 
1.4%
276837000 1
 
1.4%
1216340000 1
 
1.4%
40355806000 1
 
1.4%
5646772000 1
 
1.4%
78000 1
 
1.4%
Other values (28) 28
40.6%
ValueCountFrequency (%)
0 31
44.9%
5000 2
 
2.9%
7000 1
 
1.4%
78000 1
 
1.4%
88000 1
 
1.4%
3559000 1
 
1.4%
9022000 1
 
1.4%
237302000 1
 
1.4%
245164000 1
 
1.4%
246762000 1
 
1.4%
ValueCountFrequency (%)
44108189000 1
1.4%
40355806000 1
1.4%
37382413000 1
1.4%
35719619000 1
1.4%
33870876000 1
1.4%
30743244000 1
1.4%
25667478000 1
1.4%
20845484000 1
1.4%
20834720000 1
1.4%
16810894000 1
1.4%

비과세금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3912516 × 109
Minimum0
Maximum3.901205 × 1010
Zeros39
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:59.216234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38.16987 × 108
95-th percentile3.0585103 × 1010
Maximum3.901205 × 1010
Range3.901205 × 1010
Interquartile range (IQR)8.16987 × 108

Descriptive statistics

Standard deviation8.8652094 × 109
Coefficient of variation (CV)2.6141409
Kurtosis8.6614511
Mean3.3912516 × 109
Median Absolute Deviation (MAD)0
Skewness3.1035729
Sum2.3399636 × 1011
Variance7.8591937 × 1019
MonotonicityNot monotonic
2023-12-12T13:48:59.392825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 39
56.5%
29458209000 1
 
1.4%
5998042000 1
 
1.4%
894144000 1
 
1.4%
4301871000 1
 
1.4%
39012050000 1
 
1.4%
212373000 1
 
1.4%
112278000 1
 
1.4%
10673800000 1
 
1.4%
819860000 1
 
1.4%
Other values (21) 21
30.4%
ValueCountFrequency (%)
0 39
56.5%
31526000 1
 
1.4%
33569000 1
 
1.4%
46107000 1
 
1.4%
68379000 1
 
1.4%
112278000 1
 
1.4%
193195000 1
 
1.4%
193795000 1
 
1.4%
195521000 1
 
1.4%
212373000 1
 
1.4%
ValueCountFrequency (%)
39012050000 1
1.4%
35657635000 1
1.4%
32927489000 1
1.4%
31336365000 1
1.4%
29458209000 1
1.4%
10673800000 1
1.4%
8645835000 1
1.4%
7471386000 1
1.4%
5998042000 1
1.4%
5880312000 1
1.4%

감면금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct38
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6375969 × 109
Minimum0
Maximum2.4745202 × 1010
Zeros31
Zeros (%)44.9%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:59.579771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median78000
Q39.04929 × 108
95-th percentile1.1685564 × 1010
Maximum2.4745202 × 1010
Range2.4745202 × 1010
Interquartile range (IQR)9.04929 × 108

Descriptive statistics

Standard deviation4.2329222 × 109
Coefficient of variation (CV)2.5848377
Kurtosis14.69911
Mean1.6375969 × 109
Median Absolute Deviation (MAD)78000
Skewness3.6445805
Sum1.1299418 × 1011
Variance1.7917631 × 1019
MonotonicityNot monotonic
2023-12-12T13:48:59.778512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 31
44.9%
5000 2
 
2.9%
278890000 1
 
1.4%
7000 1
 
1.4%
286171000 1
 
1.4%
208458000 1
 
1.4%
1020819000 1
 
1.4%
4698171000 1
 
1.4%
1345193000 1
 
1.4%
78000 1
 
1.4%
Other values (28) 28
40.6%
ValueCountFrequency (%)
0 31
44.9%
5000 2
 
2.9%
7000 1
 
1.4%
78000 1
 
1.4%
88000 1
 
1.4%
3559000 1
 
1.4%
9022000 1
 
1.4%
132886000 1
 
1.4%
191195000 1
 
1.4%
208458000 1
 
1.4%
ValueCountFrequency (%)
24745202000 1
1.4%
14993678000 1
1.4%
13374098000 1
1.4%
12188885000 1
1.4%
10930582000 1
1.4%
5096139000 1
1.4%
4698171000 1
1.4%
4454924000 1
1.4%
4412667000 1
1.4%
4383254000 1
1.4%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.846957
Minimum0
Maximum90.35
Zeros38
Zeros (%)55.1%
Negative0
Negative (%)0.0%
Memory size753.0 B
2023-12-12T13:48:59.952603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314.05
95-th percentile83.636
Maximum90.35
Range90.35
Interquartile range (IQR)14.05

Descriptive statistics

Standard deviation28.281318
Coefficient of variation (CV)1.9048563
Kurtosis2.0568458
Mean14.846957
Median Absolute Deviation (MAD)0
Skewness1.9186054
Sum1024.44
Variance799.83296
MonotonicityNot monotonic
2023-12-12T13:49:00.460307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 38
55.1%
3.16 1
 
1.4%
21.34 1
 
1.4%
13.08 1
 
1.4%
81.08 1
 
1.4%
77.14 1
 
1.4%
2.65 1
 
1.4%
3.22 1
 
1.4%
20.3 1
 
1.4%
14.05 1
 
1.4%
Other values (22) 22
31.9%
ValueCountFrequency (%)
0.0 38
55.1%
2.37 1
 
1.4%
2.44 1
 
1.4%
2.51 1
 
1.4%
2.65 1
 
1.4%
2.93 1
 
1.4%
3.16 1
 
1.4%
3.22 1
 
1.4%
3.24 1
 
1.4%
4.07 1
 
1.4%
ValueCountFrequency (%)
90.35 1
1.4%
89.01 1
1.4%
88.78 1
1.4%
85.34 1
1.4%
81.08 1
1.4%
77.25 1
1.4%
77.14 1
1.4%
75.45 1
1.4%
74.09 1
1.4%
73.97 1
1.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-11-08
69 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-08
2nd row2023-11-08
3rd row2023-11-08
4th row2023-11-08
5th row2023-11-08

Common Values

ValueCountFrequency (%)
2023-11-08 69
100.0%

Length

2023-12-12T13:49:00.599642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:49:00.752212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-08 69
100.0%

Interactions

2023-12-12T13:48:52.392262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.340941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.695978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.228583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.717121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.898372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.315261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.691092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.189357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.869202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.836509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.328311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.962693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.496764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.436668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.825484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.334396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.814911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.983485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.418849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.811823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.336707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.993189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.937825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.465566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.065348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.598027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.544075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.936062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.469191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.935799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.323628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.533691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.949290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.486575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.123693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.039551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.573011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.167584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.689914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.654932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.029340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.566992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.047306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.411868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.634766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.090134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.620470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.266599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.131768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.670309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.274658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.814972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.768677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.152256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.696398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.146561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.501934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.743448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.188812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.728658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.414888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.243482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.785557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.396891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.963864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.858167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.246200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.820175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.224884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.583360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.846106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.295404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.832577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.532140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.370146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.940336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.488409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.067537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:34.945752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.377209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.946253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.303225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.670197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.959307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.411445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.952420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.631917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.465815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.085063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.594100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.186531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.059865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.507032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.058543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.391037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.758076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.077255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.515889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.089555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.767642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.577686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.215016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.719297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.287281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.178664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.641678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.184859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.484516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.850389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.211523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.629140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.232819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:46.914241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.686310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.343284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.837928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.381301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.278671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.747453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.291145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.570525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:40.937403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.308834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.727776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.353474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.402575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.820457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.482549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:51.949053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.488122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.368284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:36.868868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.386199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.644630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.023983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.394405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.851672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.463471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.510042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:48.951110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.611393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.029894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.618949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.482945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.004704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.543224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.735852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.127714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.510171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:43.973130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.603017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.633309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.102129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.750980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.190740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:53.737610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:35.581568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:37.133687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:38.633662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:39.817374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:41.224122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:42.599789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:44.075512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:45.738237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:47.738800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:49.209157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:50.853081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:48:52.290342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:49:00.843560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율과세건수과세금액비과세건수비과세감면금액비과세금액감면금액비과세감면율
과세년도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
세목명0.0001.0000.8470.8360.5550.5630.7650.7330.9330.8560.8660.7840.8190.6950.992
부과금액0.0000.8471.0000.9990.5560.0000.5530.0000.7191.0000.7460.8580.6710.9350.832
수납급액0.0000.8360.9991.0000.5140.0000.5010.0000.6521.0000.7670.8610.6830.9380.838
환급금액0.0000.5550.5560.5141.0000.9360.8740.8950.0000.5090.0000.0000.0000.0000.000
결손금액0.0000.5630.0000.0000.9361.0000.9850.9810.0000.0000.0000.0000.0000.0000.000
미수납금액0.0000.7650.5530.5010.8740.9851.0000.9430.5120.4790.5240.0000.5020.3420.356
징수율0.0000.7330.0000.0000.8950.9810.9431.0000.2980.0000.0000.0000.0000.0000.000
과세건수0.0000.9330.7190.6520.0000.0000.5120.2981.0000.7150.6970.5930.7460.6690.529
과세금액0.0000.8561.0001.0000.5090.0000.4790.0000.7151.0000.7450.8580.6700.9350.828
비과세건수0.0000.8660.7460.7670.0000.0000.5240.0000.6970.7451.0000.8690.7990.8450.878
비과세감면금액0.0000.7840.8580.8610.0000.0000.0000.0000.5930.8580.8691.0000.9980.9400.909
비과세금액0.0000.8190.6710.6830.0000.0000.5020.0000.7460.6700.7990.9981.0000.8160.790
감면금액0.0000.6950.9350.9380.0000.0000.3420.0000.6690.9350.8450.9400.8161.0000.757
비과세감면율0.0000.9920.8320.8380.0000.0000.3560.0000.5290.8280.8780.9090.7900.7571.000
2023-12-12T13:49:01.065102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도
세목명1.0000.000
과세년도0.0001.000
2023-12-12T13:49:01.204781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과금액수납급액환급금액결손금액미수납금액징수율과세건수과세금액비과세건수비과세감면금액비과세금액감면금액비과세감면율과세년도세목명
부과금액1.0000.9790.7890.5080.7180.4290.5700.9190.3870.3880.3830.4080.2340.0000.490
수납급액0.9791.0000.6980.4240.6250.5100.6340.9650.4420.4430.4370.4600.2970.0000.474
환급금액0.7890.6981.0000.8090.8990.1780.4170.5710.2860.2660.2620.2870.1760.0000.265
결손금액0.5080.4240.8091.0000.8140.0110.4160.3060.2600.2010.1900.1890.1720.0000.275
미수납금액0.7180.6250.8990.8141.000-0.0330.5090.4990.4170.3670.3450.3670.2540.0000.416
징수율0.4290.5100.1780.011-0.0331.0000.3820.5400.2290.2570.3390.2590.3290.0000.346
과세건수0.5700.6340.4170.4160.5090.3821.0000.6870.7370.6510.5700.6170.5190.0000.710
과세금액0.9190.9650.5710.3060.4990.5400.6871.0000.4920.4950.4820.5120.3500.0000.506
비과세건수0.3870.4420.2860.2600.4170.2290.7370.4921.0000.9720.9080.9580.8770.0000.571
비과세감면금액0.3880.4430.2660.2010.3670.2570.6510.4950.9721.0000.9380.9920.9140.0000.438
비과세금액0.3830.4370.2620.1900.3450.3390.5700.4820.9080.9381.0000.9200.9560.0000.513
감면금액0.4080.4600.2870.1890.3670.2590.6170.5120.9580.9920.9201.0000.8910.0000.374
비과세감면율0.2340.2970.1760.1720.2540.3290.5190.3500.8770.9140.9560.8911.0000.0000.802
과세년도0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
세목명0.4900.4740.2650.2750.4160.3460.7100.5060.5710.4380.5130.3740.8020.0001.000

Missing values

2023-12-12T13:48:53.922071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:48:54.554925image/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

시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율과세건수과세금액비과세건수비과세감면금액비과세금액감면금액비과세감면율데이터기준일
0강원특별자치도춘천시511102018도축세0000000000000.02023-11-08
1강원특별자치도춘천시511102018레저세0000000000000.02023-11-08
2강원특별자치도춘천시511102018재산세44892983000436756180001791700052800012168370009721127444892983000502843387087600029458209000441266700075.452023-11-08
3강원특별자치도춘천시511102018주민세57125090005480940000126000001020000230549000961243505712509000179735071795000420310000086869500088.782023-11-08
4강원특별자치도춘천시511102018취득세9330704900093088929000443944000513110001668090001004060493307049000106752084548400074713860001337409800022.342023-11-08
5강원특별자치도춘천시511102018자동차세51126231000480571250002698820001789000306731700094202283511262310002450912453710003404420009049290002.442023-11-08
6강원특별자치도춘천시511102018과년도수입23509157000104671480002167936000256416600010477843000450000000.02023-11-08
7강원특별자치도춘천시511102018담배소비세188527740001885277400040000001001021885277400000000.02023-11-08
8강원특별자치도춘천시511102018도시계획세0000000000000.02023-11-08
9강원특별자치도춘천시511102018등록면허세5841858000581456100074095000131000271660001009593558418580004136297454000315260002659280005.092023-11-08
시도명시군구명자치단체코드과세년도세목명부과금액수납급액환급금액결손금액미수납금액징수율과세건수과세금액비과세건수비과세감면금액비과세금액감면금액비과세감면율데이터기준일
59강원특별자치도춘천시511102022등록면허세7578451000756203400022632000016417000100101080757845100055882451640001122780001328860003.222023-11-08
60강원특별자치도춘천시511102022레저세1538740001538740000001004515387400000000.02023-11-08
61강원특별자치도춘천시511102022자동차세443157710004158314600031349100022000273260300094217494443157710003118511751850002123730009628120002.652023-11-08
62강원특별자치도춘천시511102022재산세571782250005590057100030781000500012776490009824594457178225000590794410818900039012050000509613900077.142023-11-08
63강원특별자치도춘천시511102022주민세700630900068443210002033000200001619680009811803370063090002474356808130004301871000137894200081.082023-11-08
64강원특별자치도춘천시511102022지방교육세3483385600033833615000123079000900010002320009760351034833856000372880000880000.02023-11-08
65강원특별자치도춘천시511102022지방소득세8331610700081200749000181430800026870002112671000971287158331610700000000.02023-11-08
66강원특별자치도춘천시511102022지방소비세152349980001523499800000010091523499800000000.02023-11-08
67강원특별자치도춘천시511102022지역자원시설세90143650008855449000179800001589160009813644290993410005507117898200089414400028483800013.082023-11-08
68강원특별자치도춘천시511102022취득세144081000000143694000000437604000038645900010043220144081000000127373074324400059980420002474520200021.342023-11-08