Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows8
Duplicate rows (%)0.1%
Total size in memory1.2 MiB
Average record size in memory130.0 B

Variable types

Categorical6
Numeric6
Text1
DateTime1

Dataset

Description일반건축물에 대한 지방세 부과기준인 시가표준액을 제공인천광역시 부평구 일반건축물 시가표준액 데이터입니다.(시도명,시군구명,자치단체코드,과세년도,법정동,법정리,특수지,본번,부번,동,호,물건지,시가표준액,연면적,기준일자)예) 인천광역시,부평구,28237,2019,102,00,1,0251,0002,0001,0002,[ 백범로568번길 24 ] 0001동 0002호,51303000,209.4,20190601
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15080133&srcSe=7661IVAWM27C61E190

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 8 (0.1%) duplicate rowsDuplicates
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (97.0%)Imbalance
동 is highly skewed (γ1 = 22.85463495)Skewed
연면적 is highly skewed (γ1 = 29.70148128)Skewed
부번 has 941 (9.4%) zerosZeros
동 has 5705 (57.0%) zerosZeros

Reproduction

Analysis started2024-01-28 17:28:48.417532
Analysis finished2024-01-28 17:28:53.632901
Duration5.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인천광역시
10000 

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 10000
100.0%

Length

2024-01-29T02:28:53.685914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:53.769489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 10000
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부평구
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부평구 10000
100.0%

Length

2024-01-29T02:28:53.845390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:53.925221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부평구 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
28237
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28237
2nd row28237
3rd row28237
4th row28237
5th row28237

Common Values

ValueCountFrequency (%)
28237 10000
100.0%

Length

2024-01-29T02:28:54.013706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:54.113438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28237 10000
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017
10000 

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 (%)
2017 10000
100.0%

Length

2024-01-29T02:28:54.207392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:54.282130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 10000
100.0%

법정동
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.9725
Minimum101
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:54.348441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1101
median102
Q3104
95-th percentile107
Maximum109
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.1705794
Coefficient of variation (CV)0.021079214
Kurtosis-0.53562418
Mean102.9725
Median Absolute Deviation (MAD)1
Skewness0.78836279
Sum1029725
Variance4.7114149
MonotonicityNot monotonic
2024-01-29T02:28:54.453367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
101 4185
41.9%
104 1437
 
14.4%
102 1118
 
11.2%
105 927
 
9.3%
103 816
 
8.2%
107 708
 
7.1%
106 511
 
5.1%
108 231
 
2.3%
109 67
 
0.7%
ValueCountFrequency (%)
101 4185
41.9%
102 1118
 
11.2%
103 816
 
8.2%
104 1437
 
14.4%
105 927
 
9.3%
106 511
 
5.1%
107 708
 
7.1%
108 231
 
2.3%
109 67
 
0.7%
ValueCountFrequency (%)
109 67
 
0.7%
108 231
 
2.3%
107 708
 
7.1%
106 511
 
5.1%
105 927
 
9.3%
104 1437
 
14.4%
103 816
 
8.2%
102 1118
 
11.2%
101 4185
41.9%

법정리
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

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 10000
100.0%

Length

2024-01-29T02:28:54.559696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:54.639234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

특수지
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9969 
2
 
31

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 9969
99.7%
2 31
 
0.3%

Length

2024-01-29T02:28:54.720255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:54.801880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9969
99.7%
2 31
 
0.3%

본번
Real number (ℝ)

Distinct659
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324.7521
Minimum1
Maximum950
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:55.192878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38
Q1182
median341
Q3459
95-th percentile645
Maximum950
Range949
Interquartile range (IQR)277

Descriptive statistics

Standard deviation188.51705
Coefficient of variation (CV)0.58049526
Kurtosis-0.25120158
Mean324.7521
Median Absolute Deviation (MAD)142
Skewness0.36515313
Sum3247521
Variance35538.68
MonotonicityNot monotonic
2024-01-29T02:28:55.304201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205 476
 
4.8%
539 215
 
2.1%
182 170
 
1.7%
201 159
 
1.6%
199 137
 
1.4%
425 112
 
1.1%
431 109
 
1.1%
460 103
 
1.0%
386 101
 
1.0%
10 94
 
0.9%
Other values (649) 8324
83.2%
ValueCountFrequency (%)
1 4
 
< 0.1%
2 13
 
0.1%
3 13
 
0.1%
4 1
 
< 0.1%
5 11
 
0.1%
6 12
 
0.1%
7 29
 
0.3%
8 4
 
< 0.1%
9 29
 
0.3%
10 94
0.9%
ValueCountFrequency (%)
950 22
0.2%
947 3
 
< 0.1%
945 1
 
< 0.1%
938 3
 
< 0.1%
915 3
 
< 0.1%
912 1
 
< 0.1%
911 2
 
< 0.1%
910 6
 
0.1%
908 1
 
< 0.1%
907 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct377
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.8636
Minimum0
Maximum1079
Zeros941
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:55.421923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q323
95-th percentile145
Maximum1079
Range1079
Interquartile range (IQR)21

Descriptive statistics

Standard deviation88.823506
Coefficient of variation (CV)2.7027929
Kurtosis49.079355
Mean32.8636
Median Absolute Deviation (MAD)6
Skewness6.2850685
Sum328636
Variance7889.6152
MonotonicityNot monotonic
2024-01-29T02:28:55.572377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1149
 
11.5%
0 941
 
9.4%
1 797
 
8.0%
3 689
 
6.9%
4 519
 
5.2%
9 399
 
4.0%
5 372
 
3.7%
6 300
 
3.0%
7 283
 
2.8%
12 249
 
2.5%
Other values (367) 4302
43.0%
ValueCountFrequency (%)
0 941
9.4%
1 797
8.0%
2 1149
11.5%
3 689
6.9%
4 519
5.2%
5 372
 
3.7%
6 300
 
3.0%
7 283
 
2.8%
8 236
 
2.4%
9 399
 
4.0%
ValueCountFrequency (%)
1079 2
< 0.1%
1065 1
< 0.1%
1057 1
< 0.1%
990 1
< 0.1%
983 1
< 0.1%
977 1
< 0.1%
975 1
< 0.1%
966 1
< 0.1%
965 1
< 0.1%
945 1
< 0.1%

동
Real number (ℝ)

SKEWED  ZEROS 

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.6088
Minimum0
Maximum9999
Zeros5705
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:55.705581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9999
Range9999
Interquartile range (IQR)1

Descriptive statistics

Standard deviation431.31915
Coefficient of variation (CV)19.960347
Kurtosis521.70295
Mean21.6088
Median Absolute Deviation (MAD)0
Skewness22.854635
Sum216088
Variance186036.21
MonotonicityNot monotonic
2024-01-29T02:28:55.818530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 5705
57.0%
1 3466
34.7%
2 326
 
3.3%
3 156
 
1.6%
101 77
 
0.8%
4 43
 
0.4%
7 34
 
0.3%
102 31
 
0.3%
6 20
 
0.2%
9999 17
 
0.2%
Other values (31) 125
 
1.2%
ValueCountFrequency (%)
0 5705
57.0%
1 3466
34.7%
2 326
 
3.3%
3 156
 
1.6%
4 43
 
0.4%
5 17
 
0.2%
6 20
 
0.2%
7 34
 
0.3%
8 3
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9999 17
0.2%
9001 2
 
< 0.1%
510 1
 
< 0.1%
321 4
 
< 0.1%
227 1
 
< 0.1%
209 4
 
< 0.1%
203 1
 
< 0.1%
202 3
 
< 0.1%
201 6
 
0.1%
126 7
0.1%

물건지
Text

Distinct9592
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T02:28:56.085387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length28.8686
Min length16

Characters and Unicode

Total characters288686
Distinct characters114
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9248 ?
Unique (%)92.5%

Sample

1st row인천광역시 부평구 충선로203번길 16 0000동 0704호
2nd row인천광역시 부평구 갈산동 360-2 2동 15호
3rd row인천광역시 부평구 길주로547번길 8-16 0000동 0002호
4th row인천광역시 부평구 아트센터로 50 0000동 0603호
5th row인천광역시 부평구 십정동 563-10 1동 101호
ValueCountFrequency (%)
인천광역시 10000
 
17.1%
부평구 10000
 
17.1%
0000동 4226
 
7.2%
0001동 1969
 
3.4%
1동 1497
 
2.6%
부평동 1173
 
2.0%
0001호 931
 
1.6%
청천동 824
 
1.4%
0002호 656
 
1.1%
1호 517
 
0.9%
Other values (4268) 26707
45.7%
2024-01-29T02:28:56.483699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48500
16.8%
0 42545
14.7%
1 16688
 
5.8%
부 13336
 
4.6%
동 12514
 
4.3%
평 12427
 
4.3%
천 11095
 
3.8%
인 10327
 
3.6%
광 10129
 
3.5%
시 10119
 
3.5%
Other values (104) 101006
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137484
47.6%
Decimal Number 98774
34.2%
Space Separator 48500
 
16.8%
Dash Punctuation 3906
 
1.4%
Uppercase Letter 21
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 13336
9.7%
동 12514
9.1%
평 12427
9.0%
천 11095
8.1%
인 10327
 
7.5%
광 10129
 
7.4%
시 10119
 
7.4%
구 10054
 
7.3%
역 10024
 
7.3%
호 9948
 
7.2%
Other values (88) 27511
20.0%
Decimal Number
ValueCountFrequency (%)
0 42545
43.1%
1 16688
 
16.9%
2 9155
 
9.3%
3 7101
 
7.2%
4 5446
 
5.5%
5 4567
 
4.6%
6 4019
 
4.1%
8 3228
 
3.3%
7 3034
 
3.1%
9 2991
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 16
76.2%
C 4
 
19.0%
D 1
 
4.8%
Space Separator
ValueCountFrequency (%)
48500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3906
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151180
52.4%
Hangul 137484
47.6%
Latin 22
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 13336
9.7%
동 12514
9.1%
평 12427
9.0%
천 11095
8.1%
인 10327
 
7.5%
광 10129
 
7.4%
시 10119
 
7.4%
구 10054
 
7.3%
역 10024
 
7.3%
호 9948
 
7.2%
Other values (88) 27511
20.0%
Common
ValueCountFrequency (%)
48500
32.1%
0 42545
28.1%
1 16688
 
11.0%
2 9155
 
6.1%
3 7101
 
4.7%
4 5446
 
3.6%
5 4567
 
3.0%
6 4019
 
2.7%
- 3906
 
2.6%
8 3228
 
2.1%
Other values (2) 6025
 
4.0%
Latin
ValueCountFrequency (%)
B 16
72.7%
C 4
 
18.2%
b 1
 
4.5%
D 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151202
52.4%
Hangul 137484
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48500
32.1%
0 42545
28.1%
1 16688
 
11.0%
2 9155
 
6.1%
3 7101
 
4.7%
4 5446
 
3.6%
5 4567
 
3.0%
6 4019
 
2.7%
- 3906
 
2.6%
8 3228
 
2.1%
Other values (6) 6047
 
4.0%
Hangul
ValueCountFrequency (%)
부 13336
9.7%
동 12514
9.1%
평 12427
9.0%
천 11095
8.1%
인 10327
 
7.5%
광 10129
 
7.4%
시 10119
 
7.4%
구 10054
 
7.3%
역 10024
 
7.3%
호 9948
 
7.2%
Other values (88) 27511
20.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct8205
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68500232
Minimum26460
Maximum6.3004657 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:56.611840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26460
5-th percentile1490450
Q18580320
median32742860
Q368831475
95-th percentile2.3454851 × 108
Maximum6.3004657 × 109
Range6.3004393 × 109
Interquartile range (IQR)60251155

Descriptive statistics

Standard deviation1.7259907 × 108
Coefficient of variation (CV)2.5196859
Kurtosis404.54198
Mean68500232
Median Absolute Deviation (MAD)26727915
Skewness15.340584
Sum6.8500232 × 1011
Variance2.9790438 × 1016
MonotonicityNot monotonic
2024-01-29T02:28:56.734224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1780200 143
 
1.4%
34802500 72
 
0.7%
28412280 46
 
0.5%
35937270 44
 
0.4%
5004200 43
 
0.4%
5371000 40
 
0.4%
35535290 36
 
0.4%
4805080 35
 
0.4%
5224280 28
 
0.3%
28121000 27
 
0.3%
Other values (8195) 9486
94.9%
ValueCountFrequency (%)
26460 1
< 0.1%
28050 1
< 0.1%
32670 1
< 0.1%
33660 1
< 0.1%
34000 1
< 0.1%
43650 1
< 0.1%
52020 1
< 0.1%
54450 1
< 0.1%
61710 1
< 0.1%
63150 1
< 0.1%
ValueCountFrequency (%)
6300465720 1
< 0.1%
5797609750 1
< 0.1%
4725024110 1
< 0.1%
3918721590 1
< 0.1%
3092762400 1
< 0.1%
2651398840 1
< 0.1%
2121829250 1
< 0.1%
2053473360 1
< 0.1%
2052968400 1
< 0.1%
2006064060 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6566
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.63282
Minimum0.49
Maximum31103.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:56.846054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.49
5-th percentile6.5595
Q131.08
median70.535
Q3146.225
95-th percentile490.5925
Maximum31103.67
Range31103.18
Interquartile range (IQR)115.145

Descriptive statistics

Standard deviation514.63704
Coefficient of variation (CV)3.2856272
Kurtosis1459.3508
Mean156.63282
Median Absolute Deviation (MAD)48.315
Skewness29.701481
Sum1566328.2
Variance264851.28
MonotonicityNot monotonic
2024-01-29T02:28:56.964080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3 143
 
1.4%
51.483 72
 
0.7%
42.03 46
 
0.5%
18.0 45
 
0.4%
55.89 44
 
0.4%
9.55 43
 
0.4%
10.25 40
 
0.4%
52.567 36
 
0.4%
9.17 35
 
0.4%
9.97 28
 
0.3%
Other values (6556) 9468
94.7%
ValueCountFrequency (%)
0.49 1
 
< 0.1%
0.5 1
 
< 0.1%
0.64 1
 
< 0.1%
0.6917 1
 
< 0.1%
0.81 1
 
< 0.1%
0.86 1
 
< 0.1%
0.91 1
 
< 0.1%
0.99 10
0.1%
1.0 3
 
< 0.1%
1.02 1
 
< 0.1%
ValueCountFrequency (%)
31103.67 1
< 0.1%
13439.56 1
< 0.1%
12823.94 1
< 0.1%
12561.98 1
< 0.1%
8994.12 1
< 0.1%
8885.99 1
< 0.1%
7992.26 1
< 0.1%
6497.4 1
< 0.1%
6116.36 1
< 0.1%
6081.19 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-06-01 00:00:00
Maximum2017-06-01 00:00:00
2024-01-29T02:28:57.063075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:57.138906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T02:28:52.756379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.026665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.585295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.132312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.653568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.186049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.857582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.123383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.687143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.234805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.745575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.293344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.953529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.206886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.763833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.308844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.824856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.386363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:53.050554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.298224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.870072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.391185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.901855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.474676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:53.139015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.391219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.958751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.477906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.985224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.563745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:53.228879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:50.495533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.050104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:51.565329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.087858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:52.657533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:28:57.206537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동시가표준액연면적
법정동1.0000.0940.5150.1980.0420.0530.047
특수지0.0941.0000.1610.0000.0000.0000.000
본번0.5150.1611.0000.3620.0850.0000.000
부번0.1980.0000.3621.0000.0000.0000.000
동0.0420.0000.0850.0001.0000.0000.000
시가표준액0.0530.0000.0000.0000.0001.0000.745
연면적0.0470.0000.0000.0000.0000.7451.000
2024-01-29T02:28:57.308213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적특수지
법정동1.000-0.196-0.1850.0130.0410.1440.094
본번-0.1961.000-0.1290.0680.1370.0490.123
부번-0.185-0.1291.000-0.0550.0240.0530.000
동0.0130.068-0.0551.0000.0040.1230.000
시가표준액0.0410.1370.0240.0041.0000.8740.000
연면적0.1440.0490.0530.1230.8741.0000.000
특수지0.0940.1230.0000.0000.0000.0001.000

Missing values

2024-01-29T02:28:53.357789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:28:53.540912image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동물건지시가표준액연면적기준일자
61375인천광역시부평구2823720171050146070인천광역시 부평구 충선로203번길 16 0000동 0704호1471775034.142017-06-01
486인천광역시부평구2823720171060136022인천광역시 부평구 갈산동 360-2 2동 15호78799640162.442017-06-01
31175인천광역시부평구2823720171060138250인천광역시 부평구 길주로547번길 8-16 0000동 0002호54624240114.952017-06-01
51559인천광역시부평구28237201710201479350인천광역시 부평구 아트센터로 50 0000동 0603호1861860034.12017-06-01
16617인천광역시부평구28237201710201563101인천광역시 부평구 십정동 563-10 1동 101호77204400254.82017-06-01
47830인천광역시부평구2823720171010122291인천광역시 부평구 부흥로334번길 37 0001동 0007호1601483073.532017-06-01
48299인천광역시부평구2823720171010137950인천광역시 부평구 부흥북로 60 0000동 0201호76744250118.252017-06-01
28950인천광역시부평구282372017101015341860인천광역시 부평구 광장로4번길 23 0000동 0006호227414340374.92017-06-01
34249인천광역시부평구2823720171020148220인천광역시 부평구 동암남로 30 0000동 0101호2117452027.922017-06-01
29881인천광역시부평구2823720171010190731인천광역시 부평구 길주남로65번길 12-3 0001동 0002호42994860102.322017-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동물건지시가표준액연면적기준일자
24269인천광역시부평구2823720171010118580인천광역시 부평구 경원대로 1404 0000동 0404호1390935030.572017-06-01
55085인천광역시부평구2823720171080112630인천광역시 부평구 일신로 30 0000동 0001호1900272036.62017-06-01
36172인천광역시부평구28237201710301124870인천광역시 부평구 마장로324번길 70 0000동 0102호4180216046.3852017-06-01
32027인천광역시부평구2823720171010115210인천광역시 부평구 대정로 66 0000동 0113호821202016.62017-06-01
14295인천광역시부평구2823720171050145661인천광역시 부평구 삼산동 456-6 1동 1호596076210881.92017-06-01
63132인천광역시부평구28237201710401400140인천광역시 부평구 평천로153번길 22 0000동 0008호3691950081.52017-06-01
49532인천광역시부평구2823720171040118040인천광역시 부평구 세월천로 34 0000동 0113호657153016.472017-06-01
62930인천광역시부평구28237201710501426110인천광역시 부평구 평천로 402 0000동 0501호230312920364.0162017-06-01
45572인천광역시부평구2823720171040137630인천광역시 부평구 부평북로 37 0000동 0006호144392040308.532017-06-01
25270인천광역시부평구28237201710101179131인천광역시 부평구 경원대로 1436 0001동 0003호41353800131.72017-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동물건지시가표준액연면적기준일자# duplicates
6인천광역시부평구282372017108017951인천광역시 부평구 일신동 79-5 1동179951200314.62017-06-013
0인천광역시부평구2823720171030298251인천광역시 부평구 산곡동 산 98-25 1동 1호453600018.02017-06-012
1인천광역시부평구28237201710401178140인천광역시 부평구 마장로426번길 14 0000동 0002호2308600097.02017-06-012
2인천광역시부평구2823720171050146130인천광역시 부평구 길주로 655 0000동 0001호468381010644.08832017-06-012
3인천광역시부평구2823720171060113301인천광역시 부평구 부평대로 332 0001동 0001호32849004.842017-06-012
4인천광역시부평구2823720171060113301인천광역시 부평구 부평대로 332 0001동 0001호888480014.42017-06-012
5인천광역시부평구282372017107016960인천광역시 부평구 부개동 69-6 1호5828550001189.52017-06-012
7인천광역시부평구28237201710901770인천광역시 부평구 구산동 7-7428592600793.692017-06-012