Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows15
Duplicate rows (%)0.1%
Total size in memory1.4 MiB
Average record size in memory146.0 B

Variable types

Categorical8
Numeric6
Text2

Dataset

Description2021 ~ 2022년 기준 인천광역시 중구에 소재한 일반건축물에 대한 데이터로 년도별, 물건지별 시가표준액, 연면적을 제공합니다.
URLhttps://www.data.go.kr/data/15080288/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
법정리 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 15 (0.1%) duplicate rowsDuplicates
과세년도 is highly overall correlated with 기준일자High correlation
기준일자 is highly overall correlated with 과세년도High correlation
법정동 is highly overall correlated with 본번High correlation
본번 is highly overall correlated with 법정동High correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (95.0%)Imbalance
시가표준액 is highly skewed (γ1 = 25.51510454)Skewed
연면적 is highly skewed (γ1 = 21.0970919)Skewed
부번 has 866 (8.7%) zerosZeros
동 has 2723 (27.2%) zerosZeros

Reproduction

Analysis started2023-12-12 09:39:14.993198
Analysis finished2023-12-12 09:39:21.891795
Duration6.9 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

2023-12-12T18:39:21.960645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:22.086510image/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
중구
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 10000
100.0%

Length

2023-12-12T18:39:22.187081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:22.278770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
28110
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28110
2nd row28110
3rd row28110
4th row28110
5th row28110

Common Values

ValueCountFrequency (%)
28110 10000
100.0%

Length

2023-12-12T18:39:22.375978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:22.478024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28110 10000
100.0%

과세년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
6363 
2022
3637 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2022
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 6363
63.6%
2022 3637
36.4%

Length

2023-12-12T18:39:22.573476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:22.670316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 6363
63.6%
2022 3637
36.4%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.3848
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:22.782353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile118
Q1132
median145
Q3147
95-th percentile149
Maximum152
Range51
Interquartile range (IQR)15

Descriptive statistics

Standard deviation11.387366
Coefficient of variation (CV)0.081697327
Kurtosis0.3589645
Mean139.3848
Median Absolute Deviation (MAD)2
Skewness-1.2422491
Sum1393848
Variance129.6721
MonotonicityNot monotonic
2023-12-12T18:39:22.919986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 2618
26.2%
145 2380
23.8%
118 1096
11.0%
128 533
 
5.3%
149 510
 
5.1%
146 345
 
3.5%
148 328
 
3.3%
138 264
 
2.6%
136 148
 
1.5%
150 134
 
1.3%
Other values (40) 1644
16.4%
ValueCountFrequency (%)
101 14
 
0.1%
102 13
 
0.1%
103 62
0.6%
104 37
0.4%
105 5
 
0.1%
106 5
 
0.1%
107 1
 
< 0.1%
108 3
 
< 0.1%
109 7
 
0.1%
110 6
 
0.1%
ValueCountFrequency (%)
152 118
 
1.2%
151 98
 
1.0%
150 134
 
1.3%
149 510
 
5.1%
148 328
 
3.3%
147 2618
26.2%
146 345
 
3.5%
145 2380
23.8%
144 32
 
0.3%
143 14
 
0.1%

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

2023-12-12T18:39:23.046047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:23.142321image/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
9944 
2
 
56

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 9944
99.4%
2 56
 
0.6%

Length

2023-12-12T18:39:23.228846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:23.311111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9944
99.4%
2 56
 
0.6%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct905
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1320.7641
Minimum1
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:23.422095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q157
median1504
Q32789
95-th percentile3096
Maximum3243
Range3242
Interquartile range (IQR)2732

Descriptive statistics

Standard deviation1193.2785
Coefficient of variation (CV)0.90347588
Kurtosis-1.57324
Mean1320.7641
Median Absolute Deviation (MAD)1346
Skewness0.19486164
Sum13207641
Variance1423913.6
MonotonicityNot monotonic
2023-12-12T18:39:23.560029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1873 569
 
5.7%
1886 563
 
5.6%
2850 417
 
4.2%
27 326
 
3.3%
3098 248
 
2.5%
2803 239
 
2.4%
7 211
 
2.1%
49 196
 
2.0%
2807 182
 
1.8%
1 171
 
1.7%
Other values (895) 6878
68.8%
ValueCountFrequency (%)
1 171
1.7%
2 77
 
0.8%
3 79
 
0.8%
4 98
1.0%
5 44
 
0.4%
6 81
 
0.8%
7 211
2.1%
8 29
 
0.3%
9 35
 
0.4%
10 55
 
0.5%
ValueCountFrequency (%)
3243 35
0.4%
3238 1
 
< 0.1%
3234 9
 
0.1%
3233 3
 
< 0.1%
3231 13
 
0.1%
3220 1
 
< 0.1%
3202 13
 
0.1%
3195 1
 
< 0.1%
3194 6
 
0.1%
3192 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct275
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.8877
Minimum0
Maximum580
Zeros866
Zeros (%)8.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:23.700969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q317
95-th percentile121
Maximum580
Range580
Interquartile range (IQR)15

Descriptive statistics

Standard deviation56.649491
Coefficient of variation (CV)2.4751063
Kurtosis23.712793
Mean22.8877
Median Absolute Deviation (MAD)4
Skewness4.5202588
Sum228877
Variance3209.1648
MonotonicityNot monotonic
2023-12-12T18:39:23.844668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1458
14.6%
2 942
 
9.4%
4 889
 
8.9%
0 866
 
8.7%
3 696
 
7.0%
5 552
 
5.5%
6 494
 
4.9%
7 426
 
4.3%
8 343
 
3.4%
20 184
 
1.8%
Other values (265) 3150
31.5%
ValueCountFrequency (%)
0 866
8.7%
1 1458
14.6%
2 942
9.4%
3 696
7.0%
4 889
8.9%
5 552
 
5.5%
6 494
 
4.9%
7 426
 
4.3%
8 343
 
3.4%
9 159
 
1.6%
ValueCountFrequency (%)
580 1
 
< 0.1%
552 1
 
< 0.1%
533 2
< 0.1%
525 1
 
< 0.1%
524 3
< 0.1%
509 2
< 0.1%
497 2
< 0.1%
495 2
< 0.1%
490 2
< 0.1%
484 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean866.1024
Minimum0
Maximum9281
Zeros2723
Zeros (%)27.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:24.006475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile9001
Maximum9281
Range9281
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2642.6746
Coefficient of variation (CV)3.0512265
Kurtosis5.51535
Mean866.1024
Median Absolute Deviation (MAD)0
Skewness2.7399457
Sum8661024
Variance6983729
MonotonicityNot monotonic
2023-12-12T18:39:24.186333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5036
50.4%
0 2723
27.2%
2 560
 
5.6%
9001 555
 
5.5%
3 241
 
2.4%
9002 128
 
1.3%
4 112
 
1.1%
9003 52
 
0.5%
6 41
 
0.4%
5 41
 
0.4%
Other values (107) 511
 
5.1%
ValueCountFrequency (%)
0 2723
27.2%
1 5036
50.4%
2 560
 
5.6%
3 241
 
2.4%
4 112
 
1.1%
5 41
 
0.4%
6 41
 
0.4%
7 18
 
0.2%
8 21
 
0.2%
9 9
 
0.1%
ValueCountFrequency (%)
9281 1
 
< 0.1%
9053 2
< 0.1%
9051 1
 
< 0.1%
9050 4
< 0.1%
9048 1
 
< 0.1%
9045 2
< 0.1%
9042 3
< 0.1%
9039 2
< 0.1%
9036 1
 
< 0.1%
9031 2
< 0.1%

호
Text

Distinct1430
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:39:24.600869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.8459
Min length1

Characters and Unicode

Total characters28459
Distinct characters20
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique464 ?
Unique (%)4.6%

Sample

1st row808
2nd row3
3rd row0804
4th row3
5th row508
ValueCountFrequency (%)
1 1286
 
12.8%
0001 703
 
7.0%
2 538
 
5.4%
3 328
 
3.3%
0 278
 
2.8%
4 229
 
2.3%
0000 179
 
1.8%
5 148
 
1.5%
0002 139
 
1.4%
101 126
 
1.3%
Other values (1421) 6062
60.5%
2023-12-12T18:39:25.191296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9463
33.3%
1 7138
25.1%
2 3196
 
11.2%
3 1869
 
6.6%
4 1549
 
5.4%
5 1233
 
4.3%
8 1089
 
3.8%
6 1078
 
3.8%
7 931
 
3.3%
9 798
 
2.8%
Other values (10) 115
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28344
99.6%
Dash Punctuation 53
 
0.2%
Other Letter 34
 
0.1%
Space Separator 16
 
0.1%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9463
33.4%
1 7138
25.2%
2 3196
 
11.3%
3 1869
 
6.6%
4 1549
 
5.5%
5 1233
 
4.4%
8 1089
 
3.8%
6 1078
 
3.8%
7 931
 
3.3%
9 798
 
2.8%
Other Letter
ValueCountFrequency (%)
월 16
47.1%
일 16
47.1%
부 1
 
2.9%
층 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
T 4
33.3%
A 2
16.7%
S 2
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28413
99.8%
Hangul 34
 
0.1%
Latin 12
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9463
33.3%
1 7138
25.1%
2 3196
 
11.2%
3 1869
 
6.6%
4 1549
 
5.5%
5 1233
 
4.3%
8 1089
 
3.8%
6 1078
 
3.8%
7 931
 
3.3%
9 798
 
2.8%
Other values (2) 69
 
0.2%
Hangul
ValueCountFrequency (%)
월 16
47.1%
일 16
47.1%
부 1
 
2.9%
층 1
 
2.9%
Latin
ValueCountFrequency (%)
B 4
33.3%
T 4
33.3%
A 2
16.7%
S 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28425
99.9%
Hangul 34
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9463
33.3%
1 7138
25.1%
2 3196
 
11.2%
3 1869
 
6.6%
4 1549
 
5.4%
5 1233
 
4.3%
8 1089
 
3.8%
6 1078
 
3.8%
7 931
 
3.3%
9 798
 
2.8%
Other values (6) 81
 
0.3%
Hangul
ValueCountFrequency (%)
월 16
47.1%
일 16
47.1%
부 1
 
2.9%
층 1
 
2.9%

물건지
Text

Distinct9315
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T18:39:25.504873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length25.6637
Min length16

Characters and Unicode

Total characters256637
Distinct characters157
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8745 ?
Unique (%)87.5%

Sample

1st row[ 신도시남로142번길 6 ] 0003동 0808호
2nd row인천광역시 중구 운북동 933-94 9001동 3호
3rd row[ 하늘별빛로65번길 7-9 ] 0000동 0804호
4th row[ 개항로 9 ] 0001동 0003호
5th row[ 자연대로 29 ] 0001동 0508호
ValueCountFrequency (%)
13876
23.4%
0001동 3739
 
6.3%
인천광역시 3062
 
5.2%
중구 3062
 
5.2%
0000동 2240
 
3.8%
1동 1297
 
2.2%
1호 1000
 
1.7%
0001호 988
 
1.7%
운서동 716
 
1.2%
영종대로 669
 
1.1%
Other values (3796) 28742
48.4%
2023-12-12T18:39:26.043736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49391
19.2%
0 40297
15.7%
1 20535
 
8.0%
동 12614
 
4.9%
호 9821
 
3.8%
2 9319
 
3.6%
] 6938
 
2.7%
[ 6938
 
2.7%
로 6876
 
2.7%
3 6326
 
2.5%
Other values (147) 87582
34.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103607
40.4%
Other Letter 85847
33.5%
Space Separator 49391
19.2%
Close Punctuation 6938
 
2.7%
Open Punctuation 6938
 
2.7%
Dash Punctuation 3904
 
1.5%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12614
 
14.7%
호 9821
 
11.4%
로 6876
 
8.0%
길 3669
 
4.3%
번 3591
 
4.2%
중 3582
 
4.2%
시 3454
 
4.0%
광 3232
 
3.8%
인 3227
 
3.8%
역 3073
 
3.6%
Other values (129) 32708
38.1%
Decimal Number
ValueCountFrequency (%)
0 40297
38.9%
1 20535
19.8%
2 9319
 
9.0%
3 6326
 
6.1%
4 4961
 
4.8%
9 4770
 
4.6%
5 4584
 
4.4%
6 4379
 
4.2%
7 4279
 
4.1%
8 4157
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
33.3%
T 4
33.3%
A 2
16.7%
S 2
16.7%
Space Separator
ValueCountFrequency (%)
49391
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6938
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6938
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3904
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170778
66.5%
Hangul 85847
33.5%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12614
 
14.7%
호 9821
 
11.4%
로 6876
 
8.0%
길 3669
 
4.3%
번 3591
 
4.2%
중 3582
 
4.2%
시 3454
 
4.0%
광 3232
 
3.8%
인 3227
 
3.8%
역 3073
 
3.6%
Other values (129) 32708
38.1%
Common
ValueCountFrequency (%)
49391
28.9%
0 40297
23.6%
1 20535
12.0%
2 9319
 
5.5%
] 6938
 
4.1%
[ 6938
 
4.1%
3 6326
 
3.7%
4 4961
 
2.9%
9 4770
 
2.8%
5 4584
 
2.7%
Other values (4) 16719
 
9.8%
Latin
ValueCountFrequency (%)
B 4
33.3%
T 4
33.3%
A 2
16.7%
S 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170790
66.5%
Hangul 85847
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49391
28.9%
0 40297
23.6%
1 20535
12.0%
2 9319
 
5.5%
] 6938
 
4.1%
[ 6938
 
4.1%
3 6326
 
3.7%
4 4961
 
2.9%
9 4770
 
2.8%
5 4584
 
2.7%
Other values (8) 16731
 
9.8%
Hangul
ValueCountFrequency (%)
동 12614
 
14.7%
호 9821
 
11.4%
로 6876
 
8.0%
길 3669
 
4.3%
번 3591
 
4.2%
중 3582
 
4.2%
시 3454
 
4.0%
광 3232
 
3.8%
인 3227
 
3.8%
역 3073
 
3.6%
Other values (129) 32708
38.1%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6429
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1313576 × 108
Minimum14200
Maximum3.2107815 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:26.258677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14200
5-th percentile1037595.5
Q111931790
median40577880
Q370555362
95-th percentile2.8082181 × 108
Maximum3.2107815 × 1010
Range3.2107801 × 1010
Interquartile range (IQR)58623572

Descriptive statistics

Standard deviation6.4817827 × 108
Coefficient of variation (CV)5.7292079
Kurtosis913.22854
Mean1.1313576 × 108
Median Absolute Deviation (MAD)29175305
Skewness25.515105
Sum1.1313576 × 1012
Variance4.2013507 × 1017
MonotonicityNot monotonic
2023-12-12T18:39:26.432798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40577880 71
 
0.7%
51253410 61
 
0.6%
41891550 58
 
0.6%
49637720 58
 
0.6%
37161120 51
 
0.5%
43059100 47
 
0.5%
40597430 43
 
0.4%
45863870 42
 
0.4%
40345880 41
 
0.4%
36003970 40
 
0.4%
Other values (6419) 9488
94.9%
ValueCountFrequency (%)
14200 1
< 0.1%
21300 1
< 0.1%
28400 1
< 0.1%
32400 1
< 0.1%
32670 1
< 0.1%
39600 1
< 0.1%
39760 1
< 0.1%
40800 1
< 0.1%
42600 2
< 0.1%
43200 1
< 0.1%
ValueCountFrequency (%)
32107815450 1
< 0.1%
22204671280 1
< 0.1%
18726420410 1
< 0.1%
15337514890 1
< 0.1%
14319376500 1
< 0.1%
12415666060 1
< 0.1%
11476472780 1
< 0.1%
10033186680 1
< 0.1%
9939882130 1
< 0.1%
9820366780 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2315
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.6005
Minimum0
Maximum43504
Zeros30
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:39:26.629163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q136
median54
Q3106.77453
95-th percentile510.2
Maximum43504
Range43504
Interquartile range (IQR)70.774525

Descriptive statistics

Standard deviation971.67847
Coefficient of variation (CV)5.0450465
Kurtosis649.24983
Mean192.6005
Median Absolute Deviation (MAD)27
Skewness21.097092
Sum1926005
Variance944159.05
MonotonicityNot monotonic
2023-12-12T18:39:26.814331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 447
 
4.5%
36.0 171
 
1.7%
45.0 133
 
1.3%
27.0 124
 
1.2%
40.0 120
 
1.2%
42.0 107
 
1.1%
46.0 100
 
1.0%
58.0 100
 
1.0%
35.0 99
 
1.0%
54.0 93
 
0.9%
Other values (2305) 8506
85.1%
ValueCountFrequency (%)
0.0 30
0.3%
0.3 1
 
< 0.1%
0.52 1
 
< 0.1%
0.56 1
 
< 0.1%
0.7 2
 
< 0.1%
1.0 25
0.2%
1.11 1
 
< 0.1%
1.44 1
 
< 0.1%
2.0 14
0.1%
2.4 2
 
< 0.1%
ValueCountFrequency (%)
43504.0 1
< 0.1%
30050.0 1
< 0.1%
26645.0 1
< 0.1%
21000.0 1
< 0.1%
20607.0 1
< 0.1%
19651.26 1
< 0.1%
16801.0 1
< 0.1%
16761.0 1
< 0.1%
14974.46 1
< 0.1%
14682.0 1
< 0.1%

기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-06-01
6363 
2022-06-01
3637 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-06-01
2nd row2021-06-01
3rd row2022-06-01
4th row2021-06-01
5th row2021-06-01

Common Values

ValueCountFrequency (%)
2021-06-01 6363
63.6%
2022-06-01 3637
36.4%

Length

2023-12-12T18:39:26.942199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:27.055189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 6363
63.6%
2022-06-01 3637
36.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-08-10
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-10
2nd row2023-08-10
3rd row2023-08-10
4th row2023-08-10
5th row2023-08-10

Common Values

ValueCountFrequency (%)
2023-08-10 10000
100.0%

Length

2023-12-12T18:39:27.192755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:39:27.289921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-10 10000
100.0%

Interactions

2023-12-12T18:39:20.412325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:16.926763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.658408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.410945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.057324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.699845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.529749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.039097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.818524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.527664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.149871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.800945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.689458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.196437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.940107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.633082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.261479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.910254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.796454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.332071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.058972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.742302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.377602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.052461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.936148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.437698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.159968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.836606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.479830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.148114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:21.075475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:17.550227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.304181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:18.954753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:19.602393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:39:20.265050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:39:27.369333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동특수지본번부번동시가표준액연면적기준일자
과세년도1.0000.4570.0090.4160.1330.1110.0000.0041.000
법정동0.4571.0000.0930.8500.4740.1950.0000.0000.457
특수지0.0090.0931.0000.1080.0000.4340.0000.0000.009
본번0.4160.8500.1081.0000.3800.3320.0220.0220.416
부번0.1330.4740.0000.3801.0000.0390.0000.0000.133
동0.1110.1950.4340.3320.0391.0000.0000.0000.111
시가표준액0.0000.0000.0000.0220.0000.0001.0000.8810.000
연면적0.0040.0000.0000.0220.0000.0000.8811.0000.004
기준일자1.0000.4570.0090.4160.1330.1110.0000.0041.000
2023-12-12T18:39:27.523277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도기준일자특수지
과세년도1.0001.0000.006
기준일자1.0001.0000.006
특수지0.0060.0061.000
2023-12-12T18:39:27.649768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적과세년도특수지기준일자
법정동1.0000.651-0.3050.1280.1590.0430.3510.0710.351
본번0.6511.000-0.347-0.1400.3670.0810.3200.0820.320
부번-0.305-0.3471.000-0.050-0.099-0.0690.1020.0000.102
동0.128-0.140-0.0501.000-0.258-0.0920.0730.2920.073
시가표준액0.1590.367-0.099-0.2581.0000.7730.0000.0000.000
연면적0.0430.081-0.069-0.0920.7731.0000.0050.0000.005
과세년도0.3510.3200.1020.0730.0000.0051.0000.0061.000
특수지0.0710.0820.0000.2920.0000.0000.0061.0000.006
기준일자0.3510.3200.1020.0730.0000.0051.0000.0061.000

Missing values

2023-12-12T18:39:21.569933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:39:21.796712image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
19999인천광역시중구28110202114701280313808[ 신도시남로142번길 6 ] 0003동 0808호6391890061.02021-06-012023-08-10
12639인천광역시중구281102021148019339490013인천광역시 중구 운북동 933-94 9001동 3호750000060.02021-06-012023-08-10
64326인천광역시중구281102022145011886300804[ 하늘별빛로65번길 7-9 ] 0000동 0804호332770680373.482022-06-012023-08-10
39919인천광역시중구2811020211040183413[ 개항로 9 ] 0001동 0003호1582600082.02021-06-012023-08-10
15181인천광역시중구28110202114501187381508[ 자연대로 29 ] 0001동 0508호5524045049.02021-06-012023-08-10
50090인천광역시중구28110202114701287503201인천광역시 중구 운서동 2875 3동 201호1975816038.02021-06-012023-08-10
32915인천광역시중구2811020211180127692100인천광역시 중구 항동7가 27-69 2동 100호292581017.02021-06-012023-08-10
15982인천광역시중구28110202114601429990010[ 운남동로 68 ] 9001동 0000호96480018.02021-06-012023-08-10
57734인천광역시중구2811020221450119462010121[ 영종진광장로 46 ] 0001동 0121호7293181061.3932022-06-012023-08-10
42202인천광역시중구28110202114701285051331[ 공항로424번길 60 ] 0001동 0331호3629262061.02021-06-012023-08-10
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
79700인천광역시중구2811020221420110100105인천광역시 중구 송월동1가 10-1 105호924000.72022-06-012023-08-10
25945인천광역시중구2811020211280164090208인천광역시 중구 신흥동3가 64 9020동 8호340200018.02021-06-012023-08-10
15078인천광역시중구28110202114501187331511[ 자연대로 47 ] 0001동 0511호222148810190.02021-06-012023-08-10
36050인천광역시중구281102021122013503[ 우현로9번길 63 ] 0000동 0003호598747059.02021-06-012023-08-10
57437인천광역시중구281102022147013098500730[ 영종대로196번길 25 ] 0000동 0730호6708912058.442022-06-012023-08-10
8951인천광역시중구28110202115101132411인천광역시 중구 덕교동 132-4 1동 1호205193120253.02021-06-012023-08-10
54090인천광역시중구281102022132017503010102인천광역시 중구 도원동 75 301동 102호7760040073.97562022-06-012023-08-10
46082인천광역시중구28110202113601271012[ 우현로87번길 23 ] 0001동 0002호128218013.02021-06-012023-08-10
76857인천광역시중구281102022147012803130625[ 신도시남로142번길 6 ] 0003동 0625호4607937042.82472022-06-012023-08-10
74789인천광역시중구28110202215201270230000인천광역시 중구 무의동 270-2 3동6585602.42022-06-012023-08-10

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일# duplicates
6인천광역시중구281102021127015450219인천광역시 중구 신흥동2가 54-5 219호549000.02021-06-012023-08-103
0인천광역시중구281102021118012769293인천광역시 중구 항동7가 27-69 2동 93호292581017.02021-06-012023-08-102
1인천광역시중구2811020211180145011인천광역시 중구 항동7가 45 1동 1호2220840060.02021-06-012023-08-102
2인천광역시중구28110202112301381611인천광역시 중구 신생동 38-16 1동 1호246240018.02021-06-012023-08-102
3인천광역시중구281102021127015450112인천광역시 중구 신흥동2가 54-5 112호631300.02021-06-012023-08-102
4인천광역시중구281102021127015450119인천광역시 중구 신흥동2가 54-5 119호1473101.02021-06-012023-08-102
5인천광역시중구281102021127015450124인천광역시 중구 신흥동2가 54-5 124호631300.02021-06-012023-08-102
7인천광역시중구28110202113401219002[ 개항로 78-1 ] 0000동 0002호18512000231.02021-06-012023-08-102
8인천광역시중구28110202113801988100[ 월미로 211 ] 0000동 0000호210092040230.02021-06-012023-08-102
9인천광역시중구281102021147013243014인천광역시 중구 운서동 3243 1동 4호106347600155.02021-06-012023-08-102