Overview

Dataset statistics

Number of variables22
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory197.5 B

Variable types

Categorical13
Text2
Numeric7

Dataset

Description인천광역시 미추홀구 결손사유별집계표에 대한 데이터로 세목명,자지단체명,병기세목,배분금액부족건구,배분금액부족금액 등에 대한 정보를 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15086362&srcSe=7661IVAWM27C61E190

Alerts

자치단체명 has constant value ""Constant
체납처분중지건수 has constant value ""Constant
체납처분중지금액 has constant value ""Constant
채무자회생및파산에관한법률건수 has constant value ""Constant
채무자회생및파산에관한법률금액 has constant value ""Constant
국세결손건수 has constant value ""Constant
국세결손금액 has constant value ""Constant
행방불명건수 is highly imbalanced (70.3%)Imbalance
행방불명금액 is highly imbalanced (77.9%)Imbalance
기타건수 is highly imbalanced (70.3%)Imbalance
기타금액 is highly imbalanced (73.8%)Imbalance
배분금액부족금액 has 23 (60.5%) zerosZeros
무재산건수 has 22 (57.9%) zerosZeros
무재산금액 has 22 (57.9%) zerosZeros
시효소멸건수 has 9 (23.7%) zerosZeros
시효소멸금액 has 9 (23.7%) zerosZeros
평가액부족건수 has 31 (81.6%) zerosZeros
평가액부족금액 has 31 (81.6%) zerosZeros

Reproduction

Analysis started2024-01-28 17:36:11.451679
Analysis finished2024-01-28 17:36:11.677898
Duration0.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
도세
25 
시세
11 
국세
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도세 25
65.8%
시세 11
28.9%
국세 2
 
5.3%

Length

2024-01-29T02:36:11.735652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:11.823085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도세 25
65.8%
시세 11
28.9%
국세 2
 
5.3%

세목명
Text

Distinct26
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-01-29T02:36:11.992104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length11.289474
Min length7

Characters and Unicode

Total characters429
Distinct characters43
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)47.4%

Sample

1st row재산세(주택)
2nd row재산세(건축물)
3rd row자동차세(자동차)
4th row자동차세(자동차)
5th row자동차세(이륜차)
ValueCountFrequency (%)
재산세(구)재산세(건축물 5
 
13.2%
재산세(구)재산세(주택 3
 
7.9%
재산세(주택 2
 
5.3%
자동차세(자동차세(자동차 2
 
5.3%
자동차세(자동차 2
 
5.3%
구)재산세(건축물 2
 
5.3%
재산세(건축물 2
 
5.3%
재산세(구)재산세(토지 2
 
5.3%
주민세(주민세(개인균등 1
 
2.6%
등록면허세(등록 1
 
2.6%
Other values (16) 16
42.1%
2024-01-29T02:36:12.281850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 69
16.1%
세 55
12.8%
( 55
12.8%
재 36
 
8.4%
산 36
 
8.4%
구 14
 
3.3%
차 13
 
3.0%
자 12
 
2.8%
동 12
 
2.8%
주 11
 
2.6%
Other values (33) 116
27.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 305
71.1%
Close Punctuation 69
 
16.1%
Open Punctuation 55
 
12.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 55
18.0%
재 36
 
11.8%
산 36
 
11.8%
구 14
 
4.6%
차 13
 
4.3%
자 12
 
3.9%
동 12
 
3.9%
주 11
 
3.6%
건 10
 
3.3%
축 10
 
3.3%
Other values (31) 96
31.5%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
71.1%
Common 124
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 55
18.0%
재 36
 
11.8%
산 36
 
11.8%
구 14
 
4.6%
차 13
 
4.3%
자 12
 
3.9%
동 12
 
3.9%
주 11
 
3.6%
건 10
 
3.3%
축 10
 
3.3%
Other values (31) 96
31.5%
Common
ValueCountFrequency (%)
) 69
55.6%
( 55
44.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 305
71.1%
ASCII 124
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 69
55.6%
( 55
44.4%
Hangul
ValueCountFrequency (%)
세 55
18.0%
재 36
 
11.8%
산 36
 
11.8%
구 14
 
4.6%
차 13
 
4.3%
자 12
 
3.9%
동 12
 
3.9%
주 11
 
3.6%
건 10
 
3.3%
축 10
 
3.3%
Other values (31) 96
31.5%

자치단체명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
인천광역시 미추홀구
38 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 미추홀구 38
100.0%

Length

2024-01-29T02:36:12.403868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:12.498084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 38
50.0%
미추홀구 38
50.0%

병기세목
Text

Distinct22
Distinct (%)57.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-01-29T02:36:12.658974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.2368421
Min length3

Characters and Unicode

Total characters275
Distinct characters52
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)39.5%

Sample

1st row지역자원시설세(소방)
2nd row지역자원시설세(소방)
3rd row자동차세(자동차)
4th row자동차세(자동차)
5th row자동차세(이륜차)
ValueCountFrequency (%)
지방교육세 9
23.7%
도시계획세 4
 
10.5%
지역자원시설세(소방 2
 
5.3%
공동시설세 2
 
5.3%
자동차세(자동차 2
 
5.3%
구)재산세(건축물 2
 
5.3%
교육세 2
 
5.3%
자동차세(기계장비 1
 
2.6%
지방소득세(종합소득 1
 
2.6%
주민세(개인균등 1
 
2.6%
Other values (12) 12
31.6%
2024-01-29T02:36:12.963787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 38
 
13.8%
) 25
 
9.1%
( 21
 
7.6%
지 16
 
5.8%
방 14
 
5.1%
육 11
 
4.0%
교 11
 
4.0%
자 8
 
2.9%
산 8
 
2.9%
재 8
 
2.9%
Other values (42) 115
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229
83.3%
Close Punctuation 25
 
9.1%
Open Punctuation 21
 
7.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
세 38
 
16.6%
지 16
 
7.0%
방 14
 
6.1%
육 11
 
4.8%
교 11
 
4.8%
자 8
 
3.5%
산 8
 
3.5%
재 8
 
3.5%
동 8
 
3.5%
시 8
 
3.5%
Other values (40) 99
43.2%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 229
83.3%
Common 46
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
세 38
 
16.6%
지 16
 
7.0%
방 14
 
6.1%
육 11
 
4.8%
교 11
 
4.8%
자 8
 
3.5%
산 8
 
3.5%
재 8
 
3.5%
동 8
 
3.5%
시 8
 
3.5%
Other values (40) 99
43.2%
Common
ValueCountFrequency (%)
) 25
54.3%
( 21
45.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 229
83.3%
ASCII 46
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 38
 
16.6%
지 16
 
7.0%
방 14
 
6.1%
육 11
 
4.8%
교 11
 
4.8%
자 8
 
3.5%
산 8
 
3.5%
재 8
 
3.5%
동 8
 
3.5%
시 8
 
3.5%
Other values (40) 99
43.2%
ASCII
ValueCountFrequency (%)
) 25
54.3%
( 21
45.7%

배분금액부족건수
Categorical

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
23 
5
7 
4
5 
1
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23
60.5%
5 7
 
18.4%
4 5
 
13.2%
1 3
 
7.9%

Length

2024-01-29T02:36:13.085541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:13.194532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
60.5%
5 7
 
18.4%
4 5
 
13.2%
1 3
 
7.9%

배분금액부족금액
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2188810.3
Minimum0
Maximum30092490
Zeros23
Zeros (%)60.5%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:13.292166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3253027.5
95-th percentile19518571
Maximum30092490
Range30092490
Interquartile range (IQR)253027.5

Descriptive statistics

Standard deviation6805270.8
Coefficient of variation (CV)3.1091187
Kurtosis10.794621
Mean2188810.3
Median Absolute Deviation (MAD)0
Skewness3.4067644
Sum83174790
Variance4.6311711 × 1013
MonotonicityNot monotonic
2024-01-29T02:36:13.412724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 23
60.5%
99060 1
 
2.6%
199080 1
 
2.6%
831050 1
 
2.6%
18555760 1
 
2.6%
30092490 1
 
2.6%
271010 1
 
2.6%
651870 1
 
2.6%
385690 1
 
2.6%
130340 1
 
2.6%
Other values (6) 6
 
15.8%
ValueCountFrequency (%)
0 23
60.5%
54180 1
 
2.6%
63650 1
 
2.6%
99060 1
 
2.6%
130340 1
 
2.6%
199080 1
 
2.6%
271010 1
 
2.6%
385690 1
 
2.6%
651870 1
 
2.6%
654570 1
 
2.6%
ValueCountFrequency (%)
30092490 1
2.6%
24974500 1
2.6%
18555760 1
2.6%
3760000 1
2.6%
2451540 1
2.6%
831050 1
2.6%
654570 1
2.6%
651870 1
2.6%
385690 1
2.6%
271010 1
2.6%

무재산건수
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.526316
Minimum0
Maximum473
Zeros22
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:13.528315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.75
95-th percentile84.4
Maximum473
Range473
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation104.62849
Coefficient of variation (CV)3.944328
Kurtosis16.225563
Mean26.526316
Median Absolute Deviation (MAD)0
Skewness4.1619059
Sum1008
Variance10947.121
MonotonicityNot monotonic
2024-01-29T02:36:13.617875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 22
57.9%
1 6
 
15.8%
2 2
 
5.3%
7 2
 
5.3%
19 2
 
5.3%
13 1
 
2.6%
473 1
 
2.6%
5 1
 
2.6%
455 1
 
2.6%
ValueCountFrequency (%)
0 22
57.9%
1 6
 
15.8%
2 2
 
5.3%
5 1
 
2.6%
7 2
 
5.3%
13 1
 
2.6%
19 2
 
5.3%
455 1
 
2.6%
473 1
 
2.6%
ValueCountFrequency (%)
473 1
 
2.6%
455 1
 
2.6%
19 2
 
5.3%
13 1
 
2.6%
7 2
 
5.3%
5 1
 
2.6%
2 2
 
5.3%
1 6
 
15.8%
0 22
57.9%

무재산금액
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2463551.1
Minimum0
Maximum49911610
Zeros22
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:13.720690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3153167.5
95-th percentile10661643
Maximum49911610
Range49911610
Interquartile range (IQR)153167.5

Descriptive statistics

Standard deviation8501016.4
Coefficient of variation (CV)3.4507166
Kurtosis27.74107
Mean2463551.1
Median Absolute Deviation (MAD)0
Skewness5.0469625
Sum93614940
Variance7.226728 × 1013
MonotonicityNot monotonic
2024-01-29T02:36:13.825967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 22
57.9%
86770 1
 
2.6%
8703100 1
 
2.6%
55620 1
 
2.6%
1955040 1
 
2.6%
854830 1
 
2.6%
1589870 1
 
2.6%
14150290 1
 
2.6%
16570 1
 
2.6%
73270 1
 
2.6%
Other values (7) 7
 
18.4%
ValueCountFrequency (%)
0 22
57.9%
10360 1
 
2.6%
16570 1
 
2.6%
55620 1
 
2.6%
66430 1
 
2.6%
73270 1
 
2.6%
86770 1
 
2.6%
175300 1
 
2.6%
531530 1
 
2.6%
854830 1
 
2.6%
ValueCountFrequency (%)
49911610 1
2.6%
14150290 1
2.6%
10046000 1
2.6%
8703100 1
2.6%
5388350 1
2.6%
1955040 1
2.6%
1589870 1
2.6%
854830 1
2.6%
531530 1
2.6%
175300 1
2.6%

시효소멸건수
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)39.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.342105
Minimum0
Maximum261
Zeros9
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:13.930229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q329.75
95-th percentile136.9
Maximum261
Range261
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation61.052603
Coefficient of variation (CV)2.2329152
Kurtosis10.55341
Mean27.342105
Median Absolute Deviation (MAD)3
Skewness3.2441541
Sum1039
Variance3727.4203
MonotonicityNot monotonic
2024-01-29T02:36:14.045529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 9
23.7%
1 5
13.2%
2 4
10.5%
6 4
10.5%
3 3
 
7.9%
261 2
 
5.3%
42 2
 
5.3%
32 2
 
5.3%
115 1
 
2.6%
23 1
 
2.6%
Other values (5) 5
13.2%
ValueCountFrequency (%)
0 9
23.7%
1 5
13.2%
2 4
10.5%
3 3
 
7.9%
5 1
 
2.6%
6 4
10.5%
7 1
 
2.6%
23 1
 
2.6%
32 2
 
5.3%
40 1
 
2.6%
ValueCountFrequency (%)
261 2
5.3%
115 1
 
2.6%
71 1
 
2.6%
62 1
 
2.6%
42 2
5.3%
40 1
 
2.6%
32 2
5.3%
23 1
 
2.6%
7 1
 
2.6%
6 4
10.5%

시효소멸금액
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean662432.89
Minimum0
Maximum10141610
Zeros9
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:14.162604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11122.5
median63715
Q3311410
95-th percentile2311451
Maximum10141610
Range10141610
Interquartile range (IQR)310287.5

Descriptive statistics

Standard deviation1864043.3
Coefficient of variation (CV)2.8139353
Kurtosis19.777888
Mean662432.89
Median Absolute Deviation (MAD)63715
Skewness4.3108818
Sum25172450
Variance3.4746574 × 1012
MonotonicityNot monotonic
2024-01-29T02:36:14.304789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 9
23.7%
145380 2
 
5.3%
569830 1
 
2.6%
3010 1
 
2.6%
33330 1
 
2.6%
900 1
 
2.6%
819190 1
 
2.6%
1253100 1
 
2.6%
140830 1
 
2.6%
10141610 1
 
2.6%
Other values (19) 19
50.0%
ValueCountFrequency (%)
0 9
23.7%
900 1
 
2.6%
1790 1
 
2.6%
3010 1
 
2.6%
4510 1
 
2.6%
5990 1
 
2.6%
8980 1
 
2.6%
29030 1
 
2.6%
32200 1
 
2.6%
33330 1
 
2.6%
ValueCountFrequency (%)
10141610 1
2.6%
5749480 1
2.6%
1704740 1
2.6%
1487470 1
2.6%
1253100 1
2.6%
893240 1
2.6%
819190 1
2.6%
716050 1
2.6%
569830 1
2.6%
353030 1
2.6%

행방불명건수
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
36 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 36
94.7%
3 2
 
5.3%

Length

2024-01-29T02:36:14.465823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:14.566234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
94.7%
3 2
 
5.3%

행방불명금액
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
36 
141900
 
1
1212280
 
1

Length

Max length7
Median length1
Mean length1.2894737
Min length1

Unique

Unique2 ?
Unique (%)5.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 36
94.7%
141900 1
 
2.6%
1212280 1
 
2.6%

Length

2024-01-29T02:36:14.677496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:14.774066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
94.7%
141900 1
 
2.6%
1212280 1
 
2.6%

체납처분중지건수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:14.870434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:15.297191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

체납처분중지금액
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:15.394389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:15.491017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

채무자회생및파산에관한법률건수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:15.577351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:15.683160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

채무자회생및파산에관한법률금액
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:15.785417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:15.866880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

국세결손건수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:15.957302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:16.051049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

국세결손금액
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
100.0%

Length

2024-01-29T02:36:16.138490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:16.223084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
100.0%

평가액부족건수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.394737
Minimum0
Maximum348
Zeros31
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:16.298207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile39.25
Maximum348
Range348
Interquartile range (IQR)0

Descriptive statistics

Standard deviation63.236382
Coefficient of variation (CV)4.1076624
Kurtosis22.837474
Mean15.394737
Median Absolute Deviation (MAD)0
Skewness4.7183527
Sum585
Variance3998.84
MonotonicityNot monotonic
2024-01-29T02:36:16.388838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 31
81.6%
13 2
 
5.3%
8 2
 
5.3%
348 1
 
2.6%
7 1
 
2.6%
188 1
 
2.6%
ValueCountFrequency (%)
0 31
81.6%
7 1
 
2.6%
8 2
 
5.3%
13 2
 
5.3%
188 1
 
2.6%
348 1
 
2.6%
ValueCountFrequency (%)
348 1
 
2.6%
188 1
 
2.6%
13 2
 
5.3%
8 2
 
5.3%
7 1
 
2.6%
0 31
81.6%

평가액부족금액
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean993717.11
Minimum0
Maximum27640520
Zeros31
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-01-29T02:36:16.493995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2936933.5
Maximum27640520
Range27640520
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4569346.5
Coefficient of variation (CV)4.5982368
Kurtosis33.565298
Mean993717.11
Median Absolute Deviation (MAD)0
Skewness5.6930253
Sum37761250
Variance2.0878928 × 1013
MonotonicityNot monotonic
2024-01-29T02:36:16.583278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 31
81.6%
2347630 1
 
2.6%
27640520 1
 
2.6%
974020 1
 
2.6%
71060 1
 
2.6%
17720 1
 
2.6%
6276320 1
 
2.6%
433980 1
 
2.6%
ValueCountFrequency (%)
0 31
81.6%
17720 1
 
2.6%
71060 1
 
2.6%
433980 1
 
2.6%
974020 1
 
2.6%
2347630 1
 
2.6%
6276320 1
 
2.6%
27640520 1
 
2.6%
ValueCountFrequency (%)
27640520 1
 
2.6%
6276320 1
 
2.6%
2347630 1
 
2.6%
974020 1
 
2.6%
433980 1
 
2.6%
71060 1
 
2.6%
17720 1
 
2.6%
0 31
81.6%

기타건수
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
35 
6
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 35
92.1%
6 2
 
5.3%
2 1
 
2.6%

Length

2024-01-29T02:36:16.692767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:16.786377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
92.1%
6 2
 
5.3%
2 1
 
2.6%

기타금액
Categorical

IMBALANCE 

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
0
35 
5460
 
1
17580
 
1
194620
 
1

Length

Max length6
Median length1
Mean length1.3157895
Min length1

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st row5460
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 35
92.1%
5460 1
 
2.6%
17580 1
 
2.6%
194620 1
 
2.6%

Length

2024-01-29T02:36:16.894370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:36:16.991215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
92.1%
5460 1
 
2.6%
17580 1
 
2.6%
194620 1
 
2.6%

Sample

구분세목명자치단체명병기세목배분금액부족건수배분금액부족금액무재산건수무재산금액시효소멸건수시효소멸금액행방불명건수행방불명금액체납처분중지건수체납처분중지금액채무자회생및파산에관한법률건수채무자회생및파산에관한법률금액국세결손건수국세결손금액평가액부족건수평가액부족금액기타건수기타금액
0도세재산세(주택)인천광역시 미추홀구지역자원시설세(소방)1990601386770115569830000000000025460
1도세재산세(건축물)인천광역시 미추홀구지역자원시설세(소방)5249745000023353030000000000000
2도세자동차세(자동차)인천광역시 미추홀구자동차세(자동차)000011860600000000013234763000
3도세자동차세(자동차)인천광역시 미추홀구자동차세(자동차)0047349911610715749480000000003482764052000
4도세자동차세(이륜차)인천광역시 미추홀구자동차세(이륜차)0011036000000000000000
5도세자동차세(기계장비)인천광역시 미추홀구자동차세(기계장비)00002127200000000000000
6도세지방소득세(특별징수)인천광역시 미추홀구지방소득세(특별징수)00153153000000000000000
7도세지방소득세(법인소득)인천광역시 미추홀구지방소득세(법인소득)0051004600000000000000000
8도세지방소득세(종합소득)인천광역시 미추홀구지방소득세(종합소득)00253883500000000000797402000
9도세주민세(개인균등)인천광역시 미추홀구주민세(개인균등)00766430000000000087106000
구분세목명자치단체명병기세목배분금액부족건수배분금액부족금액무재산건수무재산금액시효소멸건수시효소멸금액행방불명건수행방불명금액체납처분중지건수체납처분중지금액채무자회생및파산에관한법률건수채무자회생및파산에관한법률금액국세결손건수국세결손금액평가액부족건수평가액부족금액기타건수기타금액
28시세구)재산세(주택)인천광역시 미추홀구구)재산세(주택)00006145380000000000000
29시세재산세(건축물)인천광역시 미추홀구재산세(건축물)5300924900032716050000000000000
30시세재산세(토지)인천광역시 미추홀구재산세(토지)4185557601854830421487470312122800000000000
31시세재산세(주택)인천광역시 미추홀구재산세(주택)18310501919550402611014161000000000006194620
32시세면허세(일반)인천광역시 미추홀구면허세(일반)00007140830000000000000
33시세등록면허세(면허)인천광역시 미추홀구등록면허세(면허)00255620401253100000000000000
34시세등록면허세(등록)인천광역시 미추홀구등록면허세(등록)001870310000000000000000
35시세주민세(재산분)인천광역시 미추홀구주민세(재산분)00005819190000000000000
36국세재산세(구)재산세(건축물))인천광역시 미추홀구교육세00001900000000000000
37국세자동차세(자동차세(자동차))인천광역시 미추홀구교육세0000133330000000001343398000