Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells142
Missing cells (%)0.1%
Duplicate rows74
Duplicate rows (%)0.7%
Total size in memory1.2 MiB
Average record size in memory128.0 B

Variable types

Categorical5
Numeric5
Unsupported2
Text2

Dataset

Description일반건축물에 대한 지방세 부과기준인 시가표준액( 물건지,연면적,시가표준금액 등)을 5개년(2018~2022) 데이터를 제공합니다. (물건별 재산가액 확인 가능합니다)
Author전라남도 담양군
URLhttps://www.data.go.kr/data/15080337/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
Dataset has 74 (0.7%) duplicate rowsDuplicates
특수지 is highly imbalanced (89.2%)Imbalance
동 has 142 (1.4%) missing valuesMissing
동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시가표준액 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부번 has 3398 (34.0%) zerosZeros

Reproduction

Analysis started2023-12-12 13:34:43.424211
Analysis finished2023-12-12 13:34:48.316602
Duration4.89 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
담양군
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담양군 10000
100.0%

Length

2023-12-12T22:34:48.377815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:48.468863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
담양군 10000
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담양군 10000
100.0%

Length

2023-12-12T22:34:48.587202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:48.680976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
담양군 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
46710
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row46710
2nd row46710
3rd row46710
4th row46710
5th row46710

Common Values

ValueCountFrequency (%)
46710 10000
100.0%

Length

2023-12-12T22:34:48.813247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:48.935487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46710 10000
100.0%

과세년도
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
2078 
2020
2077 
2022
1976 
2018
1940 
2019
1929 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2019
3rd row2020
4th row2022
5th row2019

Common Values

ValueCountFrequency (%)
2021 2078
20.8%
2020 2077
20.8%
2022 1976
19.8%
2018 1940
19.4%
2019 1929
19.3%

Length

2023-12-12T22:34:49.031019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:49.147485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 2078
20.8%
2020 2077
20.8%
2022 1976
19.8%
2018 1940
19.4%
2019 1929
19.3%

법정동
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean333.7775
Minimum250
Maximum410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:34:49.252080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile250
Q1250
median350
Q3380
95-th percentile410
Maximum410
Range160
Interquartile range (IQR)130

Descriptive statistics

Standard deviation56.414637
Coefficient of variation (CV)0.16901869
Kurtosis-1.2177496
Mean333.7775
Median Absolute Deviation (MAD)40
Skewness-0.42659938
Sum3337775
Variance3182.6113
MonotonicityNot monotonic
2023-12-12T22:34:49.358898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
250 2626
26.3%
340 879
 
8.8%
370 860
 
8.6%
410 773
 
7.7%
360 764
 
7.6%
390 728
 
7.3%
380 716
 
7.2%
400 646
 
6.5%
320 592
 
5.9%
310 530
 
5.3%
Other values (3) 886
 
8.9%
ValueCountFrequency (%)
250 2626
26.3%
310 530
 
5.3%
320 592
 
5.9%
330 86
 
0.9%
335 285
 
2.9%
340 879
 
8.8%
350 515
 
5.1%
360 764
 
7.6%
370 860
 
8.6%
380 716
 
7.2%
ValueCountFrequency (%)
410 773
7.7%
400 646
6.5%
390 728
7.3%
380 716
7.2%
370 860
8.6%
360 764
7.6%
350 515
5.1%
340 879
8.8%
335 285
 
2.9%
330 86
 
0.9%

법정리
Real number (ℝ)

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.0387
Minimum21
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:34:49.472677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q122
median25
Q329
95-th percentile35
Maximum39
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.3512637
Coefficient of variation (CV)0.16710756
Kurtosis-0.18280907
Mean26.0387
Median Absolute Deviation (MAD)3
Skewness0.79878276
Sum260387
Variance18.933496
MonotonicityNot monotonic
2023-12-12T22:34:49.583989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
21 1557
15.6%
24 1120
11.2%
22 1057
10.6%
23 902
9.0%
27 813
8.1%
25 778
7.8%
29 572
 
5.7%
28 543
 
5.4%
26 537
 
5.4%
30 522
 
5.2%
Other values (9) 1599
16.0%
ValueCountFrequency (%)
21 1557
15.6%
22 1057
10.6%
23 902
9.0%
24 1120
11.2%
25 778
7.8%
26 537
 
5.4%
27 813
8.1%
28 543
 
5.4%
29 572
 
5.7%
30 522
 
5.2%
ValueCountFrequency (%)
39 8
 
0.1%
38 101
 
1.0%
37 113
 
1.1%
36 49
 
0.5%
35 366
3.7%
34 149
 
1.5%
33 313
3.1%
32 195
 
1.9%
31 305
3.0%
30 522
5.2%

특수지
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9857 
2
 
143

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 9857
98.6%
2 143
 
1.4%

Length

2023-12-12T22:34:49.703916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:49.815706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9857
98.6%
2 143
 
1.4%

본번
Real number (ℝ)

Distinct1108
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean409.7276
Minimum1
Maximum1932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:34:49.937626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30
Q1149
median339
Q3601
95-th percentile1031
Maximum1932
Range1931
Interquartile range (IQR)452

Descriptive statistics

Standard deviation327.11767
Coefficient of variation (CV)0.79837842
Kurtosis1.3062262
Mean409.7276
Median Absolute Deviation (MAD)217
Skewness1.1329489
Sum4097276
Variance107005.97
MonotonicityNot monotonic
2023-12-12T22:34:50.083411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 62
 
0.6%
636 55
 
0.5%
670 45
 
0.4%
11 43
 
0.4%
301 41
 
0.4%
31 41
 
0.4%
95 40
 
0.4%
68 39
 
0.4%
579 38
 
0.4%
132 38
 
0.4%
Other values (1098) 9558
95.6%
ValueCountFrequency (%)
1 62
0.6%
2 20
 
0.2%
3 13
 
0.1%
4 12
 
0.1%
5 24
 
0.2%
6 9
 
0.1%
7 29
0.3%
8 18
 
0.2%
9 7
 
0.1%
10 10
 
0.1%
ValueCountFrequency (%)
1932 1
 
< 0.1%
1895 1
 
< 0.1%
1880 1
 
< 0.1%
1799 5
0.1%
1793 1
 
< 0.1%
1782 1
 
< 0.1%
1769 1
 
< 0.1%
1760 1
 
< 0.1%
1756 2
 
< 0.1%
1755 2
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct85
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5065
Minimum0
Maximum188
Zeros3398
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:34:50.231161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile19
Maximum188
Range188
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.278204
Coefficient of variation (CV)2.5026525
Kurtosis82.883647
Mean4.5065
Median Absolute Deviation (MAD)1
Skewness7.4473931
Sum45065
Variance127.19788
MonotonicityNot monotonic
2023-12-12T22:34:50.357599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3398
34.0%
1 2203
22.0%
2 850
 
8.5%
3 663
 
6.6%
4 557
 
5.6%
5 357
 
3.6%
6 303
 
3.0%
7 215
 
2.1%
8 177
 
1.8%
9 123
 
1.2%
Other values (75) 1154
 
11.5%
ValueCountFrequency (%)
0 3398
34.0%
1 2203
22.0%
2 850
 
8.5%
3 663
 
6.6%
4 557
 
5.6%
5 357
 
3.6%
6 303
 
3.0%
7 215
 
2.1%
8 177
 
1.8%
9 123
 
1.2%
ValueCountFrequency (%)
188 4
< 0.1%
187 1
 
< 0.1%
186 3
 
< 0.1%
142 3
 
< 0.1%
123 1
 
< 0.1%
116 1
 
< 0.1%
114 4
< 0.1%
108 2
 
< 0.1%
103 8
0.1%
98 1
 
< 0.1%

동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing142
Missing (%)1.4%
Memory size156.2 KiB

호
Real number (ℝ)

Distinct112
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean232.4414
Minimum0
Maximum9999
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:34:50.497524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median101
Q3102
95-th percentile202
Maximum9999
Range9999
Interquartile range (IQR)99

Descriptive statistics

Standard deviation1134.9671
Coefficient of variation (CV)4.8828098
Kurtosis56.014564
Mean232.4414
Median Absolute Deviation (MAD)3
Skewness7.5520306
Sum2324414
Variance1288150.4
MonotonicityNot monotonic
2023-12-12T22:34:50.626322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 3237
32.4%
1 1504
15.0%
102 1176
 
11.8%
2 657
 
6.6%
201 624
 
6.2%
103 566
 
5.7%
3 402
 
4.0%
104 265
 
2.6%
4 214
 
2.1%
105 169
 
1.7%
Other values (102) 1186
 
11.9%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 1504
15.0%
2 657
6.6%
3 402
 
4.0%
4 214
 
2.1%
5 117
 
1.2%
6 74
 
0.7%
7 42
 
0.4%
8 28
 
0.3%
9 8
 
0.1%
ValueCountFrequency (%)
9999 62
0.6%
8201 2
 
< 0.1%
8104 3
 
< 0.1%
8103 2
 
< 0.1%
8102 8
 
0.1%
8101 93
0.9%
2024 2
 
< 0.1%
1014 2
 
< 0.1%
801 2
 
< 0.1%
705 1
 
< 0.1%

물건지
Text

Distinct7498
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:34:50.958404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length19.2914
Min length8

Characters and Unicode

Total characters192914
Distinct characters244
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5964 ?
Unique (%)59.6%

Sample

1st row금성면 대성리 865-7
2nd row담양군 담양읍 백동리 15 1동 101호
3rd row[ 용산로 516-70 ] 0001동 0101호
4th row용면 월계리 149-1
5th row담양군 대덕면 매산리 303-6 1동 105호
ValueCountFrequency (%)
담양군 4061
 
8.4%
1동 3918
 
8.1%
3770
 
7.8%
담양읍 1899
 
3.9%
0001동 1847
 
3.8%
101호 1312
 
2.7%
금성면 843
 
1.7%
창평면 719
 
1.5%
무정면 664
 
1.4%
0101호 663
 
1.4%
Other values (4125) 28541
59.2%
2023-12-12T22:34:51.486809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38237
19.8%
1 20264
 
10.5%
0 15147
 
7.9%
리 8174
 
4.2%
동 6841
 
3.5%
2 6520
 
3.4%
면 6236
 
3.2%
담 6112
 
3.2%
양 6106
 
3.2%
호 6050
 
3.1%
Other values (234) 73227
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80006
41.5%
Decimal Number 64835
33.6%
Space Separator 38237
19.8%
Dash Punctuation 6048
 
3.1%
Close Punctuation 1894
 
1.0%
Open Punctuation 1894
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 8174
 
10.2%
동 6841
 
8.6%
면 6236
 
7.8%
담 6112
 
7.6%
양 6106
 
7.6%
호 6050
 
7.6%
군 4063
 
5.1%
산 2211
 
2.8%
대 1949
 
2.4%
읍 1943
 
2.4%
Other values (218) 30321
37.9%
Decimal Number
ValueCountFrequency (%)
1 20264
31.3%
0 15147
23.4%
2 6520
 
10.1%
3 4727
 
7.3%
4 3769
 
5.8%
5 3254
 
5.0%
6 3184
 
4.9%
7 2783
 
4.3%
8 2632
 
4.1%
9 2555
 
3.9%
Close Punctuation
ValueCountFrequency (%)
] 1885
99.5%
) 9
 
0.5%
Open Punctuation
ValueCountFrequency (%)
[ 1885
99.5%
( 9
 
0.5%
Space Separator
ValueCountFrequency (%)
38237
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6048
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112908
58.5%
Hangul 80006
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 8174
 
10.2%
동 6841
 
8.6%
면 6236
 
7.8%
담 6112
 
7.6%
양 6106
 
7.6%
호 6050
 
7.6%
군 4063
 
5.1%
산 2211
 
2.8%
대 1949
 
2.4%
읍 1943
 
2.4%
Other values (218) 30321
37.9%
Common
ValueCountFrequency (%)
38237
33.9%
1 20264
17.9%
0 15147
 
13.4%
2 6520
 
5.8%
- 6048
 
5.4%
3 4727
 
4.2%
4 3769
 
3.3%
5 3254
 
2.9%
6 3184
 
2.8%
7 2783
 
2.5%
Other values (6) 8975
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112908
58.5%
Hangul 80006
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38237
33.9%
1 20264
17.9%
0 15147
 
13.4%
2 6520
 
5.8%
- 6048
 
5.4%
3 4727
 
4.2%
4 3769
 
3.3%
5 3254
 
2.9%
6 3184
 
2.8%
7 2783
 
2.5%
Other values (6) 8975
 
7.9%
Hangul
ValueCountFrequency (%)
리 8174
 
10.2%
동 6841
 
8.6%
면 6236
 
7.8%
담 6112
 
7.6%
양 6106
 
7.6%
호 6050
 
7.6%
군 4063
 
5.1%
산 2211
 
2.8%
대 1949
 
2.4%
읍 1943
 
2.4%
Other values (218) 30321
37.9%

시가표준액
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

연면적
Text

Distinct4469
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:34:51.957355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.2346
Min length1

Characters and Unicode

Total characters42346
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2779 ?
Unique (%)27.8%

Sample

1st row13.05
2nd row168
3rd row155.4
4th row18
5th row328.8
ValueCountFrequency (%)
18 248
 
2.5%
0 204
 
2.0%
10 114
 
1.1%
198 63
 
0.6%
96 51
 
0.5%
72 43
 
0.4%
15 39
 
0.4%
48 38
 
0.4%
330 38
 
0.4%
99 37
 
0.4%
Other values (4459) 9125
91.2%
2023-12-12T22:34:52.562102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6901
16.3%
1 5489
13.0%
2 4109
9.7%
4 3617
8.5%
6 3463
8.2%
3 3455
8.2%
8 3438
8.1%
5 3402
8.0%
9 3057
7.2%
0 2787
6.6%
Other values (2) 2628
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35365
83.5%
Other Punctuation 6981
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5489
15.5%
2 4109
11.6%
4 3617
10.2%
6 3463
9.8%
3 3455
9.8%
8 3438
9.7%
5 3402
9.6%
9 3057
8.6%
0 2787
7.9%
7 2548
7.2%
Other Punctuation
ValueCountFrequency (%)
. 6901
98.9%
, 80
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 42346
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6901
16.3%
1 5489
13.0%
2 4109
9.7%
4 3617
8.5%
6 3463
8.2%
3 3455
8.2%
8 3438
8.1%
5 3402
8.0%
9 3057
7.2%
0 2787
6.6%
Other values (2) 2628
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6901
16.3%
1 5489
13.0%
2 4109
9.7%
4 3617
8.5%
6 3463
8.2%
3 3455
8.2%
8 3438
8.1%
5 3402
8.0%
9 3057
7.2%
0 2787
6.6%
Other values (2) 2628
 
6.2%

Interactions

2023-12-12T22:34:47.372085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:44.623460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.231788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.813049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.805950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.470105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:44.751703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.337085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.284569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.940316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.572117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:44.883172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.445567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.421637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.052338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.690906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.001343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.558896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.555773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.157205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.803498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.105723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:45.696776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:46.693499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:34:47.268811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:34:53.016415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동법정리특수지본번부번호
과세년도1.0000.0940.0820.0000.0620.0270.200
법정동0.0941.0000.4040.0590.3260.1600.029
법정리0.0820.4041.0000.0740.5400.1100.068
특수지0.0000.0590.0741.0000.1860.0020.000
본번0.0620.3260.5400.1861.0000.1500.019
부번0.0270.1600.1100.0020.1501.0000.052
호0.2000.0290.0680.0000.0190.0521.000
2023-12-12T22:34:53.133752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도특수지
과세년도1.0000.000
특수지0.0001.000
2023-12-12T22:34:53.247144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리본번부번호과세년도특수지
법정동1.000-0.2000.104-0.042-0.1240.0590.090
법정리-0.2001.0000.158-0.0870.0050.0300.068
본번0.1040.1581.000-0.046-0.0090.0260.142
부번-0.042-0.087-0.0461.000-0.0250.0150.002
호-0.1240.005-0.009-0.0251.0000.0760.000
과세년도0.0590.0300.0260.0150.0761.0000.000
특수지0.0900.0680.1420.0020.0000.0001.000

Missing values

2023-12-12T22:34:47.952750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:34:48.213437image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적
85749담양군담양군46710202237023186571.0103금성면 대성리 865-75,598,45013.05
21944담양군담양군4671020192502511501101담양군 담양읍 백동리 15 1동 101호7392000168
50882담양군담양군467102020350281612101101[ 용산로 516-70 ] 0001동 0101호4506600155.4
87823담양군담양군4671020223802617703.0101용면 월계리 149-17,524,00018
29554담양군담양군46710201935021130361105담양군 대덕면 매산리 303-6 1동 105호39784800328.8
56076담양군담양군46710202125023113831302담양읍 지침리 138-3827838024.42
23073담양군담양군46710201933522131041101담양군 가사문학면 지곡리 310-4 1동 101호102361070138.87
87867담양군담양군467102022380261149141.0401용면 월계리 149-1469,429,360157.08
60985담양군담양군467102021310211738175101봉산면 대추리 738-17164500047
16091담양군담양군46710201831021135921102[ 대추2길 10-3 ] 0001동 0102호5208008.4
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적
35050담양군담양군46710201937024135811101[ 금성문화길 27 ] 0001동 0101호3106512073.44
77013담양군담양군46710202225032155511.0101담양읍 오계리 555-1104,737,000171.7
68155담양군담양군46710202137027178004.0102금성면 봉서리 78020966409.36
83465담양군담양군46710202235023190701.0101대덕면 비차리 9071,580,00010
40091담양군담양군4671020202502116561705[ 담주2길 16 ] 0001동 0705호5736385075.5782
46368담양군담양군46710202031028188391101담양군 봉산면 와우리 883-9 1동 101호100000010
25972담양군담양군467102019400211366111담양군 수북면 나산리 366-1 1동 1호25500025.5
83453담양군담양군46710202235023130601.0104대덕면 비차리 275-171,400,000510
73577담양군담양군46710202141028159401.0105대전면 월본리 594792000055
44557담양군담양군4671020203802511742011담양군 용면 도림리 174-20 1동 1호126699680118.19

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번호물건지연면적# duplicates
28담양군담양군4671020213502711191101대덕면 운암리 119-132.485
4담양군담양군46710202032029163601담양군 고서면 동운리 636 1동 1호21.644
7담양군담양군4671020212502313109999담양읍 지침리 3104
3담양군담양군4671020193502711191101담양군 대덕면 운암리 119-1 1동 101호32.483
15담양군담양군4671020212502516702201담양읍 백동리 670-2 동산병원483.843
0담양군담양군4671020183402913530101담양군 창평면 유곡리 353 1동 101호1442
1담양군담양군4671020183702412672101담양군 금성면 원율리 267-2 1동 101호29.212
2담양군담양군4671020184102117702101담양군 대전면 대치리 770-2 1동 101호491.792
5담양군담양군467102020320291636017담양군 고서면 동운리 636 1동 17호30.82
6담양군담양군4671020212502211821103담양읍 천변리 182-192