Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
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 12 (0.1%) duplicate rowsDuplicates
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (96.9%)Imbalance
시가표준액 is highly skewed (γ1 = 23.37146685)Skewed
연면적 is highly skewed (γ1 = 25.61749697)Skewed
부번 has 978 (9.8%) zerosZeros
동 has 5632 (56.3%) zerosZeros

Reproduction

Analysis started2024-01-28 17:28:31.793272
Analysis finished2024-01-28 17:28:37.123456
Duration5.33 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

2024-01-29T02:28:37.182109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:37.260666image/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

2024-01-29T02:28:37.338723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:37.412146image/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

2024-01-29T02:28:37.502594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:37.588748image/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

2024-01-29T02:28:37.679383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:37.773520image/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%
Mean102.9407
Minimum101
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:37.850177image/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 deviation2.1524978
Coefficient of variation (CV)0.020910076
Kurtosis-0.51782096
Mean102.9407
Median Absolute Deviation (MAD)1
Skewness0.80678342
Sum1029407
Variance4.6332468
MonotonicityNot monotonic
2024-01-29T02:28:37.944823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
101 4202
42.0%
104 1403
 
14.0%
102 1170
 
11.7%
105 879
 
8.8%
103 843
 
8.4%
107 705
 
7.0%
106 521
 
5.2%
108 225
 
2.2%
109 52
 
0.5%
ValueCountFrequency (%)
101 4202
42.0%
102 1170
 
11.7%
103 843
 
8.4%
104 1403
 
14.0%
105 879
 
8.8%
106 521
 
5.2%
107 705
 
7.0%
108 225
 
2.2%
109 52
 
0.5%
ValueCountFrequency (%)
109 52
 
0.5%
108 225
 
2.2%
107 705
 
7.0%
106 521
 
5.2%
105 879
 
8.8%
104 1403
 
14.0%
103 843
 
8.4%
102 1170
 
11.7%
101 4202
42.0%

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

2024-01-29T02:28:38.062807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:38.186142image/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
9968 
2
 
32

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 9968
99.7%
2 32
 
0.3%

Length

2024-01-29T02:28:38.336794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:28:38.458007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9968
99.7%
2 32
 
0.3%

본번
Real number (ℝ)

Distinct664
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean326.8882
Minimum1
Maximum950
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:38.605855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1182
median331
Q3459
95-th percentile654
Maximum950
Range949
Interquartile range (IQR)277

Descriptive statistics

Standard deviation189.32465
Coefficient of variation (CV)0.57917248
Kurtosis-0.13379757
Mean326.8882
Median Absolute Deviation (MAD)134
Skewness0.41594036
Sum3268882
Variance35843.823
MonotonicityNot monotonic
2024-01-29T02:28:38.787246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205 477
 
4.8%
539 207
 
2.1%
182 162
 
1.6%
201 139
 
1.4%
425 130
 
1.3%
199 125
 
1.2%
431 111
 
1.1%
408 105
 
1.1%
10 104
 
1.0%
386 99
 
1.0%
Other values (654) 8341
83.4%
ValueCountFrequency (%)
1 3
 
< 0.1%
2 9
 
0.1%
3 14
 
0.1%
4 1
 
< 0.1%
5 12
 
0.1%
6 10
 
0.1%
7 19
 
0.2%
8 3
 
< 0.1%
9 30
 
0.3%
10 104
1.0%
ValueCountFrequency (%)
950 30
0.3%
949 1
 
< 0.1%
947 3
 
< 0.1%
944 1
 
< 0.1%
938 2
 
< 0.1%
915 6
 
0.1%
914 1
 
< 0.1%
912 3
 
< 0.1%
911 4
 
< 0.1%
910 2
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct391
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.5475
Minimum0
Maximum1079
Zeros978
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:38.904796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median7
Q323.25
95-th percentile145.05
Maximum1079
Range1079
Interquartile range (IQR)21.25

Descriptive statistics

Standard deviation92.868893
Coefficient of variation (CV)2.7682806
Kurtosis48.553491
Mean33.5475
Median Absolute Deviation (MAD)6
Skewness6.2900895
Sum335475
Variance8624.6312
MonotonicityNot monotonic
2024-01-29T02:28:39.032384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1162
 
11.6%
0 978
 
9.8%
1 799
 
8.0%
3 713
 
7.1%
4 501
 
5.0%
5 391
 
3.9%
9 365
 
3.6%
7 289
 
2.9%
6 270
 
2.7%
12 244
 
2.4%
Other values (381) 4288
42.9%
ValueCountFrequency (%)
0 978
9.8%
1 799
8.0%
2 1162
11.6%
3 713
7.1%
4 501
5.0%
5 391
 
3.9%
6 270
 
2.7%
7 289
 
2.9%
8 235
 
2.4%
9 365
 
3.6%
ValueCountFrequency (%)
1079 1
 
< 0.1%
1069 1
 
< 0.1%
1065 1
 
< 0.1%
1057 1
 
< 0.1%
1046 2
< 0.1%
1007 2
< 0.1%
1004 2
< 0.1%
991 1
 
< 0.1%
977 1
 
< 0.1%
975 3
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.8371
Minimum0
Maximum9999
Zeros5632
Zeros (%)56.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:39.146729image/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 deviation556.04067
Coefficient of variation (CV)16.43287
Kurtosis316.95752
Mean33.8371
Median Absolute Deviation (MAD)0
Skewness17.84718
Sum338371
Variance309181.23
MonotonicityNot monotonic
2024-01-29T02:28:39.262019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 5632
56.3%
1 3504
35.0%
2 347
 
3.5%
3 171
 
1.7%
101 83
 
0.8%
4 46
 
0.5%
7 36
 
0.4%
102 34
 
0.3%
9999 28
 
0.3%
99 11
 
0.1%
Other values (30) 108
 
1.1%
ValueCountFrequency (%)
0 5632
56.3%
1 3504
35.0%
2 347
 
3.5%
3 171
 
1.7%
4 46
 
0.5%
5 11
 
0.1%
6 10
 
0.1%
7 36
 
0.4%
8 8
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
9999 28
0.3%
9998 1
 
< 0.1%
9992 2
 
< 0.1%
801 1
 
< 0.1%
510 2
 
< 0.1%
321 3
 
< 0.1%
307 1
 
< 0.1%
227 1
 
< 0.1%
226 1
 
< 0.1%
209 2
 
< 0.1%

물건지
Text

Distinct9643
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T02:28:39.546981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length28.9199
Min length16

Characters and Unicode

Total characters289199
Distinct characters111
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

Unique9350 ?
Unique (%)93.5%

Sample

1st row인천광역시 부평구 부개동 496-6 207호
2nd row인천광역시 부평구 부평대로 301 0000동 0109-1호
3rd row인천광역시 부평구 일신동 309-1 2호
4th row인천광역시 부평구 마장로72번길 10 0001동 0001호
5th row인천광역시 부평구 경원대로 1411 0000동 0002호
ValueCountFrequency (%)
인천광역시 10000
 
17.1%
부평구 10000
 
17.1%
0000동 4180
 
7.1%
0001동 1964
 
3.4%
1동 1540
 
2.6%
부평동 1190
 
2.0%
0001호 995
 
1.7%
청천동 843
 
1.4%
0002호 677
 
1.2%
1호 510
 
0.9%
Other values (4291) 26621
45.5%
2024-01-29T02:28:39.944587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48520
16.8%
0 42414
14.7%
1 16766
 
5.8%
부 13333
 
4.6%
동 12607
 
4.4%
평 12421
 
4.3%
천 11117
 
3.8%
인 10343
 
3.6%
시 10146
 
3.5%
광 10130
 
3.5%
Other values (101) 101402
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137597
47.6%
Decimal Number 99115
34.3%
Space Separator 48520
 
16.8%
Dash Punctuation 3937
 
1.4%
Uppercase Letter 29
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 13333
9.7%
동 12607
9.2%
평 12421
9.0%
천 11117
8.1%
인 10343
 
7.5%
시 10146
 
7.4%
광 10130
 
7.4%
구 10040
 
7.3%
역 10022
 
7.3%
호 9946
 
7.2%
Other values (85) 27492
20.0%
Decimal Number
ValueCountFrequency (%)
0 42414
42.8%
1 16766
 
16.9%
2 9258
 
9.3%
3 7206
 
7.3%
4 5434
 
5.5%
5 4676
 
4.7%
6 3942
 
4.0%
8 3225
 
3.3%
7 3121
 
3.1%
9 3073
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 23
79.3%
C 4
 
13.8%
A 2
 
6.9%
Space Separator
ValueCountFrequency (%)
48520
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3937
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151572
52.4%
Hangul 137597
47.6%
Latin 30
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 13333
9.7%
동 12607
9.2%
평 12421
9.0%
천 11117
8.1%
인 10343
 
7.5%
시 10146
 
7.4%
광 10130
 
7.4%
구 10040
 
7.3%
역 10022
 
7.3%
호 9946
 
7.2%
Other values (85) 27492
20.0%
Common
ValueCountFrequency (%)
48520
32.0%
0 42414
28.0%
1 16766
 
11.1%
2 9258
 
6.1%
3 7206
 
4.8%
4 5434
 
3.6%
5 4676
 
3.1%
6 3942
 
2.6%
- 3937
 
2.6%
8 3225
 
2.1%
Other values (2) 6194
 
4.1%
Latin
ValueCountFrequency (%)
B 23
76.7%
C 4
 
13.3%
A 2
 
6.7%
b 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151602
52.4%
Hangul 137597
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48520
32.0%
0 42414
28.0%
1 16766
 
11.1%
2 9258
 
6.1%
3 7206
 
4.8%
4 5434
 
3.6%
5 4676
 
3.1%
6 3942
 
2.6%
- 3937
 
2.6%
8 3225
 
2.1%
Other values (6) 6224
 
4.1%
Hangul
ValueCountFrequency (%)
부 13333
9.7%
동 12607
9.2%
평 12421
9.0%
천 11117
8.1%
인 10343
 
7.5%
시 10146
 
7.4%
광 10130
 
7.4%
구 10040
 
7.3%
역 10022
 
7.3%
호 9946
 
7.2%
Other values (85) 27492
20.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8237
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72577180
Minimum19070
Maximum9.8346689 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:40.076834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19070
5-th percentile1521825
Q18903700
median32607815
Q368465918
95-th percentile2.361897 × 108
Maximum9.8346689 × 109
Range9.8346498 × 109
Interquartile range (IQR)59562218

Descriptive statistics

Standard deviation2.3510703 × 108
Coefficient of variation (CV)3.2394071
Kurtosis810.92504
Mean72577180
Median Absolute Deviation (MAD)26511925
Skewness23.371467
Sum7.257718 × 1011
Variance5.5275315 × 1016
MonotonicityNot monotonic
2024-01-29T02:28:40.204185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1780200 136
 
1.4%
34802500 54
 
0.5%
28412280 45
 
0.4%
4805080 43
 
0.4%
5004200 40
 
0.4%
5224280 40
 
0.4%
5371000 37
 
0.4%
35937270 35
 
0.4%
35535290 34
 
0.3%
61231390 33
 
0.3%
Other values (8227) 9503
95.0%
ValueCountFrequency (%)
19070 1
 
< 0.1%
28050 1
 
< 0.1%
34000 3
< 0.1%
37800 1
 
< 0.1%
39600 1
 
< 0.1%
41080 1
 
< 0.1%
45180 1
 
< 0.1%
57200 1
 
< 0.1%
59400 1
 
< 0.1%
61140 1
 
< 0.1%
ValueCountFrequency (%)
9834668920 1
< 0.1%
9688721580 1
< 0.1%
8078699670 1
< 0.1%
6632480660 1
< 0.1%
5200963170 1
< 0.1%
3661442350 1
< 0.1%
3092762400 1
< 0.1%
2644213070 1
< 0.1%
2252505150 1
< 0.1%
2178391400 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6577
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean161.97611
Minimum0.3
Maximum29425.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T02:28:40.336092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile6.55
Q131.95
median71.915
Q3145.275
95-th percentile509.081
Maximum29425.25
Range29424.95
Interquartile range (IQR)113.325

Descriptive statistics

Standard deviation536.09088
Coefficient of variation (CV)3.309691
Kurtosis1075.1285
Mean161.97611
Median Absolute Deviation (MAD)47.87
Skewness25.617497
Sum1619761.1
Variance287393.43
MonotonicityNot monotonic
2024-01-29T02:28:40.456712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3 136
 
1.4%
51.483 54
 
0.5%
18.0 46
 
0.5%
42.03 45
 
0.4%
9.17 43
 
0.4%
9.97 40
 
0.4%
9.55 40
 
0.4%
10.25 38
 
0.4%
55.89 35
 
0.4%
52.567 34
 
0.3%
Other values (6567) 9489
94.9%
ValueCountFrequency (%)
0.3 1
 
< 0.1%
0.34 1
 
< 0.1%
0.5 1
 
< 0.1%
0.79 2
 
< 0.1%
0.81 1
 
< 0.1%
0.91 1
 
< 0.1%
0.99 4
< 0.1%
1.0 7
0.1%
1.08 1
 
< 0.1%
1.09 1
 
< 0.1%
ValueCountFrequency (%)
29425.25 1
< 0.1%
15205.15 1
< 0.1%
13778.61 1
< 0.1%
12561.98 1
< 0.1%
10258.31 1
< 0.1%
9831.69 1
< 0.1%
9179.67 1
< 0.1%
8974.94 1
< 0.1%
8500.146 1
< 0.1%
6794.0 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
2024-01-29T02:28:40.561413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:40.650281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T02:28:36.224192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.148280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.749568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.330789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.864457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.406576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.331573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.246768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.852611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.443650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.955932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.509600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.413328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.344756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.940335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.522330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.041773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.592159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.518965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.439120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.028887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.612778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.127360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.964436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.607058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.540781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.127693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.694807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.217493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.049198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.693762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:33.650642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.235696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:34.780760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:35.303717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:28:36.139184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:28:40.713914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동시가표준액연면적
법정동1.0000.1210.5160.2030.1140.0710.101
특수지0.1211.0000.1890.0000.0000.0000.025
본번0.5160.1891.0000.3800.0610.0000.000
부번0.2030.0000.3801.0000.0390.0000.000
동0.1140.0000.0610.0391.0000.0000.000
시가표준액0.0710.0000.0000.0000.0001.0000.806
연면적0.1010.0250.0000.0000.0000.8061.000
2024-01-29T02:28:40.821375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적특수지
법정동1.000-0.191-0.1870.0350.0450.1460.121
본번-0.1911.000-0.1380.0610.1420.0600.145
부번-0.187-0.1381.000-0.0610.0150.0460.000
동0.0350.061-0.0611.0000.0170.1390.000
시가표준액0.0450.1420.0150.0171.0000.8720.000
연면적0.1460.0600.0460.1390.8721.0000.027
특수지0.1210.1450.0000.0000.0000.0271.000

Missing values

2024-01-29T02:28:36.849538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:28:37.044941image/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
3124인천광역시부평구2823720171070149660인천광역시 부평구 부개동 496-6 207호1740780034.22017-06-01
40846인천광역시부평구2823720171040144040인천광역시 부평구 부평대로 301 0000동 0109-1호98644210120.712017-06-01
17435인천광역시부평구2823720171080130910인천광역시 부평구 일신동 309-1 2호25166400117.62017-06-01
36580인천광역시부평구28237201710201174161인천광역시 부평구 마장로72번길 10 0001동 0001호4792320099.842017-06-01
24407인천광역시부평구2823720171010115940인천광역시 부평구 경원대로 1411 0000동 0002호40400450145.852017-06-01
61172인천광역시부평구28237201710701139180인천광역시 부평구 충선로 39 0000동 0001호723300075.582017-06-01
12289인천광역시부평구2823720171030129435126인천광역시 부평구 산곡동 294-35 126동 114호481800012.02017-06-01
62603인천광역시부평구2823720171060116990인천광역시 부평구 평천로 321 0000동 0004호132807160172.032017-06-01
3814인천광역시부평구28237201710101185210인천광역시 부평구 부평동 185-21 4호2189600092.02017-06-01
795인천광역시부평구2823720171060136900인천광역시 부평구 갈산동 369 107호995359020.382017-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동물건지시가표준액연면적기준일자
17703인천광역시부평구2823720171080179101인천광역시 부평구 일신동 79-10 1동 6호464400054.02017-06-01
23077인천광역시부평구282372017104019131인천광역시 부평구 청천동 9-13 1동 2호53347930145.642017-06-01
63727인천광역시부평구282372017103013112420인천광역시 부평구 화랑남로 14 0000동 0002호83743920140.042017-06-01
20831인천광역시부평구28237201710401400101인천광역시 부평구 청천동 400-10 1동 2호8347570102.552017-06-01
42514인천광역시부평구28237201710101207351인천광역시 부평구 부평대로38번길 31 0001동 0002호44734140132.92017-06-01
26301인천광역시부평구2823720171010115330인천광역시 부평구 경원대로1403번길 33 0000동 0102호66539590283.632017-06-01
55735인천광역시부평구2823720171010137831인천광역시 부평구 장제로 145 0001동 0606호1219140026.052017-06-01
38133인천광역시부평구28237201710201182921인천광역시 부평구 백운로 61 0001동 0501호5506992080.162017-06-01
15055인천광역시부평구282372017102012162021인천광역시 부평구 십정동 216-202 1동 6호2049580073.622017-06-01
21073인천광역시부평구2823720171040141140인천광역시 부평구 청천동 411-4 1호8302275601673.84592017-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동물건지시가표준액연면적기준일자# duplicates
0인천광역시부평구28237201710101182220인천광역시 부평구 경원대로1418번길 15 0000동 0000호131199650166.22282017-06-012
1인천광역시부평구28237201710101182220인천광역시 부평구 경원대로1418번길 15 0000동 0000호145777390166.22282017-06-012
2인천광역시부평구28237201710101442151인천광역시 부평구 부평대로 88 0001동 0001호609740710657.532017-06-012
3인천광역시부평구2823720171010190501인천광역시 부평구 부평동 905 1동 1호61380009.92017-06-012
4인천광역시부평구2823720171030111610인천광역시 부평구 산곡동 116-1 1호23181903.992017-06-012
5인천광역시부평구2823720171030114850인천광역시 부평구 산곡동 148-5 2호131730300187.652017-06-012
6인천광역시부평구28237201710401174100인천광역시 부평구 청천동 174-10 1호133385920167.362017-06-012
7인천광역시부평구28237201710401396181인천광역시 부평구 청천동 396-18 1동 1호43659000189.02017-06-012
8인천광역시부평구2823720171050145810인천광역시 부평구 체육관로 60 0000동 0001호1656622028.272017-06-012
9인천광역시부평구2823720171050146450인천광역시 부평구 길주로 643 0000동 0001호742715130673.42632017-06-012