Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)0.1%
Total size in memory1.4 MiB
Average record size in memory146.0 B

Variable types

Categorical6
Numeric6
Text2
DateTime2

Dataset

Description2021 ~ 2022년 기준 인천광역시 중구에 소재한 일반건축물에 대한 데이터로 년도별, 물건지별 시가표준액, 연면적을 제공합니다.
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15080288&srcSe=7661IVAWM27C61E190

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 12 (0.1%) duplicate rowsDuplicates
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 (95.9%)Imbalance
시가표준액 is highly skewed (γ1 = 43.618971)Skewed
연면적 is highly skewed (γ1 = 35.78961549)Skewed
부번 has 900 (9.0%) zerosZeros
동 has 2819 (28.2%) zerosZeros

Reproduction

Analysis started2024-04-17 10:19:32.494948
Analysis finished2024-04-17 10:19:36.985200
Duration4.49 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

2024-04-17T19:19:37.034612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:37.103014image/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

2024-04-17T19:19:37.177125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:37.246315image/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

2024-04-17T19:19:37.317520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:37.389712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28110 10000
100.0%

과세년도
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
6537 
2022
3463 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 6537
65.4%
2022 3463
34.6%

Length

2024-04-17T19:19:37.467096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:37.539989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 6537
65.4%
2022 3463
34.6%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.5647
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:37.630770image/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 deviation11.241639
Coefficient of variation (CV)0.080547869
Kurtosis0.32982694
Mean139.5647
Median Absolute Deviation (MAD)2
Skewness-1.2395031
Sum1395647
Variance126.37445
MonotonicityNot monotonic
2024-04-17T19:19:37.739433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 2610
26.1%
145 2417
24.2%
118 1036
 
10.4%
128 557
 
5.6%
149 551
 
5.5%
148 310
 
3.1%
146 308
 
3.1%
138 255
 
2.5%
151 130
 
1.3%
150 130
 
1.3%
Other values (42) 1696
17.0%
ValueCountFrequency (%)
101 10
 
0.1%
102 10
 
0.1%
103 51
0.5%
104 27
0.3%
105 5
 
0.1%
106 9
 
0.1%
107 3
 
< 0.1%
108 2
 
< 0.1%
109 9
 
0.1%
110 6
 
0.1%
ValueCountFrequency (%)
152 127
 
1.3%
151 130
 
1.3%
150 130
 
1.3%
149 551
 
5.5%
148 310
 
3.1%
147 2610
26.1%
146 308
 
3.1%
145 2417
24.2%
144 27
 
0.3%
143 19
 
0.2%

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

2024-04-17T19:19:37.838064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:37.925179image/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
9956 
2
 
44

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 9956
99.6%
2 44
 
0.4%

Length

2024-04-17T19:19:38.022864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:19:38.124515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9956
99.6%
2 44
 
0.4%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct899
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1329.7528
Minimum1
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:38.246477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q157
median1566
Q32789
95-th percentile3096
Maximum3243
Range3242
Interquartile range (IQR)2732

Descriptive statistics

Standard deviation1188.9698
Coefficient of variation (CV)0.89412843
Kurtosis-1.5671183
Mean1329.7528
Median Absolute Deviation (MAD)1285
Skewness0.18092806
Sum13297528
Variance1413649.1
MonotonicityNot monotonic
2024-04-17T19:19:38.385879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1873 570
 
5.7%
1886 554
 
5.5%
2850 428
 
4.3%
27 310
 
3.1%
3098 253
 
2.5%
7 219
 
2.2%
2807 214
 
2.1%
2803 210
 
2.1%
49 172
 
1.7%
1 164
 
1.6%
Other values (889) 6906
69.1%
ValueCountFrequency (%)
1 164
1.6%
2 83
 
0.8%
3 87
 
0.9%
4 79
 
0.8%
5 45
 
0.4%
6 95
0.9%
7 219
2.2%
8 30
 
0.3%
9 41
 
0.4%
10 62
 
0.6%
ValueCountFrequency (%)
3243 38
0.4%
3234 6
 
0.1%
3231 12
 
0.1%
3220 1
 
< 0.1%
3212 2
 
< 0.1%
3203 2
 
< 0.1%
3202 8
 
0.1%
3198 1
 
< 0.1%
3196 1
 
< 0.1%
3194 7
 
0.1%

부번
Real number (ℝ)

ZEROS 

Distinct273
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5791
Minimum0
Maximum580
Zeros900
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:38.555828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q316
95-th percentile117
Maximum580
Range580
Interquartile range (IQR)14

Descriptive statistics

Standard deviation58.020725
Coefficient of variation (CV)2.5696651
Kurtosis27.120352
Mean22.5791
Median Absolute Deviation (MAD)4
Skewness4.8094132
Sum225791
Variance3366.4046
MonotonicityNot monotonic
2024-04-17T19:19:38.981287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1475
14.8%
4 901
 
9.0%
0 900
 
9.0%
2 890
 
8.9%
3 741
 
7.4%
5 545
 
5.5%
6 476
 
4.8%
7 439
 
4.4%
8 323
 
3.2%
18 178
 
1.8%
Other values (263) 3132
31.3%
ValueCountFrequency (%)
0 900
9.0%
1 1475
14.8%
2 890
8.9%
3 741
7.4%
4 901
9.0%
5 545
 
5.5%
6 476
 
4.8%
7 439
 
4.4%
8 323
 
3.2%
9 159
 
1.6%
ValueCountFrequency (%)
580 5
0.1%
577 2
 
< 0.1%
565 1
 
< 0.1%
552 1
 
< 0.1%
533 2
 
< 0.1%
525 1
 
< 0.1%
524 3
< 0.1%
509 1
 
< 0.1%
497 1
 
< 0.1%
496 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct114
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean775.4053
Minimum0
Maximum9054
Zeros2819
Zeros (%)28.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:39.167568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile9001
Maximum9054
Range9054
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2513.3783
Coefficient of variation (CV)3.2413737
Kurtosis6.713713
Mean775.4053
Median Absolute Deviation (MAD)0
Skewness2.9502497
Sum7754053
Variance6317070.6
MonotonicityNot monotonic
2024-04-17T19:19:39.279826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5063
50.6%
0 2819
28.2%
2 541
 
5.4%
9001 518
 
5.2%
3 248
 
2.5%
9002 129
 
1.3%
4 116
 
1.2%
9003 47
 
0.5%
5 41
 
0.4%
8001 36
 
0.4%
Other values (104) 442
 
4.4%
ValueCountFrequency (%)
0 2819
28.2%
1 5063
50.6%
2 541
 
5.4%
3 248
 
2.5%
4 116
 
1.2%
5 41
 
0.4%
6 33
 
0.3%
7 24
 
0.2%
8 14
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
9054 1
 
< 0.1%
9050 2
 
< 0.1%
9045 2
 
< 0.1%
9044 1
 
< 0.1%
9041 1
 
< 0.1%
9035 1
 
< 0.1%
9033 1
 
< 0.1%
9027 1
 
< 0.1%
9024 7
0.1%
9022 3
< 0.1%

호
Text

Distinct1447
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T19:19:39.581770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.8006
Min length1

Characters and Unicode

Total characters28006
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

Unique500 ?
Unique (%)5.0%

Sample

1st row1
2nd row0012
3rd row0601
4th row8103
5th row0918
ValueCountFrequency (%)
1 1400
 
14.0%
0001 606
 
6.1%
2 584
 
5.8%
3 347
 
3.5%
0 323
 
3.2%
4 212
 
2.1%
0000 156
 
1.6%
0002 141
 
1.4%
5 136
 
1.4%
101 105
 
1.0%
Other values (1439) 6005
60.0%
2024-04-17T19:19:39.985649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9047
32.3%
1 7163
25.6%
2 3215
 
11.5%
3 1869
 
6.7%
4 1460
 
5.2%
5 1194
 
4.3%
8 1098
 
3.9%
6 1054
 
3.8%
7 957
 
3.4%
9 838
 
3.0%
Other values (10) 111
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27895
99.6%
Dash Punctuation 52
 
0.2%
Other Letter 33
 
0.1%
Space Separator 15
 
0.1%
Uppercase Letter 11
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9047
32.4%
1 7163
25.7%
2 3215
 
11.5%
3 1869
 
6.7%
4 1460
 
5.2%
5 1194
 
4.3%
8 1098
 
3.9%
6 1054
 
3.8%
7 957
 
3.4%
9 838
 
3.0%
Other Letter
ValueCountFrequency (%)
월 15
45.5%
일 15
45.5%
부 1
 
3.0%
층 1
 
3.0%
비 1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
54.5%
S 3
27.3%
T 2
 
18.2%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27962
99.8%
Hangul 33
 
0.1%
Latin 11
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9047
32.4%
1 7163
25.6%
2 3215
 
11.5%
3 1869
 
6.7%
4 1460
 
5.2%
5 1194
 
4.3%
8 1098
 
3.9%
6 1054
 
3.8%
7 957
 
3.4%
9 838
 
3.0%
Other values (2) 67
 
0.2%
Hangul
ValueCountFrequency (%)
월 15
45.5%
일 15
45.5%
부 1
 
3.0%
층 1
 
3.0%
비 1
 
3.0%
Latin
ValueCountFrequency (%)
B 6
54.5%
S 3
27.3%
T 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27973
99.9%
Hangul 33
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9047
32.3%
1 7163
25.6%
2 3215
 
11.5%
3 1869
 
6.7%
4 1460
 
5.2%
5 1194
 
4.3%
8 1098
 
3.9%
6 1054
 
3.8%
7 957
 
3.4%
9 838
 
3.0%
Other values (5) 78
 
0.3%
Hangul
ValueCountFrequency (%)
월 15
45.5%
일 15
45.5%
부 1
 
3.0%
층 1
 
3.0%
비 1
 
3.0%

물건지
Text

Distinct9310
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T19:19:40.236051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length25.6341
Min length16

Characters and Unicode

Total characters256341
Distinct characters156
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

Unique8730 ?
Unique (%)87.3%

Sample

1st row[ 자연대로 145 ] 9006동 0001호
2nd row인천광역시 중구 신흥동3가 7-206 1동 12호
3rd row[ 영종대로 166 ] 0001동 0601호
4th row[ 큰우물로 28-24 ] 0001동 8103호
5th row[ 영종대로 911 ] 0000동 0918호
ValueCountFrequency (%)
13800
23.2%
0001동 3687
 
6.2%
인천광역시 3100
 
5.2%
중구 3100
 
5.2%
0000동 2328
 
3.9%
1동 1376
 
2.3%
0001호 1043
 
1.8%
1호 963
 
1.6%
운서동 750
 
1.3%
영종대로 668
 
1.1%
Other values (3778) 28541
48.1%
2024-04-17T19:19:40.589963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49356
19.3%
0 40087
15.6%
1 20457
 
8.0%
동 12654
 
4.9%
호 9809
 
3.8%
2 9308
 
3.6%
[ 6900
 
2.7%
] 6900
 
2.7%
로 6841
 
2.7%
3 6411
 
2.5%
Other values (146) 87618
34.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103154
40.2%
Other Letter 86123
33.6%
Space Separator 49356
19.3%
Open Punctuation 6900
 
2.7%
Close Punctuation 6900
 
2.7%
Dash Punctuation 3897
 
1.5%
Uppercase Letter 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12654
 
14.7%
호 9809
 
11.4%
로 6841
 
7.9%
길 3632
 
4.2%
중 3607
 
4.2%
번 3557
 
4.1%
시 3471
 
4.0%
광 3301
 
3.8%
인 3279
 
3.8%
역 3109
 
3.6%
Other values (129) 32863
38.2%
Decimal Number
ValueCountFrequency (%)
0 40087
38.9%
1 20457
19.8%
2 9308
 
9.0%
3 6411
 
6.2%
4 4774
 
4.6%
9 4759
 
4.6%
5 4477
 
4.3%
6 4376
 
4.2%
7 4373
 
4.2%
8 4132
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
54.5%
S 3
27.3%
T 2
 
18.2%
Space Separator
ValueCountFrequency (%)
49356
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6900
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6900
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3897
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170207
66.4%
Hangul 86123
33.6%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12654
 
14.7%
호 9809
 
11.4%
로 6841
 
7.9%
길 3632
 
4.2%
중 3607
 
4.2%
번 3557
 
4.1%
시 3471
 
4.0%
광 3301
 
3.8%
인 3279
 
3.8%
역 3109
 
3.6%
Other values (129) 32863
38.2%
Common
ValueCountFrequency (%)
49356
29.0%
0 40087
23.6%
1 20457
12.0%
2 9308
 
5.5%
[ 6900
 
4.1%
] 6900
 
4.1%
3 6411
 
3.8%
4 4774
 
2.8%
9 4759
 
2.8%
5 4477
 
2.6%
Other values (4) 16778
 
9.9%
Latin
ValueCountFrequency (%)
B 6
54.5%
S 3
27.3%
T 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170218
66.4%
Hangul 86123
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49356
29.0%
0 40087
23.6%
1 20457
12.0%
2 9308
 
5.5%
[ 6900
 
4.1%
] 6900
 
4.1%
3 6411
 
3.8%
4 4774
 
2.8%
9 4759
 
2.8%
5 4477
 
2.6%
Other values (7) 16789
 
9.9%
Hangul
ValueCountFrequency (%)
동 12654
 
14.7%
호 9809
 
11.4%
로 6841
 
7.9%
길 3632
 
4.2%
중 3607
 
4.2%
번 3557
 
4.1%
시 3471
 
4.0%
광 3301
 
3.8%
인 3279
 
3.8%
역 3109
 
3.6%
Other values (129) 32863
38.2%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6444
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5959255 × 108
Minimum21300
Maximum1.17832 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:40.711130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21300
5-th percentile1120000
Q113446000
median41462210
Q372424770
95-th percentile3.0600536 × 108
Maximum1.17832 × 1011
Range1.1783198 × 1011
Interquartile range (IQR)58978770

Descriptive statistics

Standard deviation1.9065514 × 109
Coefficient of variation (CV)11.946368
Kurtosis2278.8237
Mean1.5959255 × 108
Median Absolute Deviation (MAD)28908700
Skewness43.618971
Sum1.5959255 × 1012
Variance3.6349381 × 1018
MonotonicityNot monotonic
2024-04-17T19:19:40.826019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41891550 66
 
0.7%
40577880 62
 
0.6%
51253410 58
 
0.6%
49637720 58
 
0.6%
40597430 57
 
0.6%
36003970 51
 
0.5%
37161120 51
 
0.5%
43059100 47
 
0.5%
43281090 43
 
0.4%
46017400 38
 
0.4%
Other values (6434) 9469
94.7%
ValueCountFrequency (%)
21300 1
 
< 0.1%
26400 2
 
< 0.1%
34320 1
 
< 0.1%
35640 1
 
< 0.1%
42600 2
 
< 0.1%
43920 5
0.1%
47520 1
 
< 0.1%
54900 6
0.1%
56800 1
 
< 0.1%
57960 1
 
< 0.1%
ValueCountFrequency (%)
117832000000 1
< 0.1%
95293013860 1
< 0.1%
66515933260 1
< 0.1%
44681139400 1
< 0.1%
39957802830 1
< 0.1%
25851875280 1
< 0.1%
25851862960 1
< 0.1%
24571443960 1
< 0.1%
20534534320 1
< 0.1%
18859696240 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2298
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean253.01578
Minimum0
Maximum123126
Zeros21
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T19:19:40.946343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q136.4909
median55
Q3115
95-th percentile545.42675
Maximum123126
Range123126
Interquartile range (IQR)78.5091

Descriptive statistics

Standard deviation2381.2823
Coefficient of variation (CV)9.4115963
Kurtosis1571.4611
Mean253.01578
Median Absolute Deviation (MAD)27
Skewness35.789615
Sum2530157.8
Variance5670505.6
MonotonicityNot monotonic
2024-04-17T19:19:41.065002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 371
 
3.7%
45.0 163
 
1.6%
36.0 157
 
1.6%
27.0 136
 
1.4%
40.0 133
 
1.3%
58.0 131
 
1.3%
35.0 108
 
1.1%
49.0 106
 
1.1%
46.0 105
 
1.1%
39.0 105
 
1.1%
Other values (2288) 8485
84.9%
ValueCountFrequency (%)
0.0 21
0.2%
0.2 2
 
< 0.1%
0.25 1
 
< 0.1%
0.26 1
 
< 0.1%
0.27 1
 
< 0.1%
0.52 1
 
< 0.1%
0.7 1
 
< 0.1%
1.0 20
0.2%
1.5 1
 
< 0.1%
1.95 1
 
< 0.1%
ValueCountFrequency (%)
123126.0 1
< 0.1%
118039.0 1
< 0.1%
83521.0 1
< 0.1%
68524.0 1
< 0.1%
41967.0 2
< 0.1%
41753.0 1
< 0.1%
39436.0 1
< 0.1%
35137.0 1
< 0.1%
30616.0 1
< 0.1%
29635.0 1
< 0.1%

기준일자
Date

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-06-01 00:00:00
Maximum2022-06-01 00:00:00
2024-04-17T19:19:41.145647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:41.217753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-08-10 00:00:00
Maximum2023-08-10 00:00:00
2024-04-17T19:19:41.291583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:41.364800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T19:19:36.210943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:33.691443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.356878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.822245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.292879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.725775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.291119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:33.768814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.429394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.900180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.364678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.803729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.366216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:33.843064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.516565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.976690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.438327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.883174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.450730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:33.924694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.590185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.051551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.512595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.970329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.524439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:33.996736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.661994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.123384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.576262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.054282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.604351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.070290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:34.742181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.206714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:35.654613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:19:36.135320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T19:19:41.433800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동특수지본번부번동시가표준액연면적기준일자
과세년도1.0000.4470.0000.4310.1340.0860.0000.0061.000
법정동0.4471.0000.0890.8500.5000.1820.0000.0000.447
특수지0.0000.0891.0000.0960.0000.2740.0000.0000.000
본번0.4310.8500.0961.0000.3520.2990.0840.0820.431
부번0.1340.5000.0000.3521.0000.0600.0000.0000.134
동0.0860.1820.2740.2990.0601.0000.0000.0000.086
시가표준액0.0000.0000.0000.0840.0000.0001.0000.9780.000
연면적0.0060.0000.0000.0820.0000.0000.9781.0000.006
기준일자1.0000.4470.0000.4310.1340.0860.0000.0061.000
2024-04-17T19:19:41.538569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도특수지
과세년도1.0000.000
특수지0.0001.000
2024-04-17T19:19:41.607947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적과세년도특수지
법정동1.0000.644-0.2920.1310.1620.0560.3430.069
본번0.6441.000-0.339-0.1360.3490.0590.3310.073
부번-0.292-0.3391.000-0.035-0.107-0.0820.1010.000
동0.131-0.136-0.0351.000-0.236-0.0670.0570.183
시가표준액0.1620.349-0.107-0.2361.0000.7680.0000.000
연면적0.0560.059-0.082-0.0670.7681.0000.0070.000
과세년도0.3430.3310.1010.0570.0000.0071.0000.000
특수지0.0690.0730.0000.1830.0000.0000.0001.000

Missing values

2024-04-17T19:19:36.717461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T19:19:36.898726image/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
17162인천광역시중구28110202114501864690061[ 자연대로 145 ] 9006동 0001호324000027.02021-06-012023-08-10
56345인천광역시중구28110202212801720610012인천광역시 중구 신흥동3가 7-206 1동 12호20428798802721.012022-06-012023-08-10
61633인천광역시중구281102022147013087210601[ 영종대로 166 ] 0001동 0601호5795359051.2472022-06-012023-08-10
28519인천광역시중구28110202113501104018103[ 큰우물로 28-24 ] 0001동 8103호3173387057.02021-06-012023-08-10
67319인천광역시중구281102022145011886700918[ 영종대로 911 ] 0000동 0918호4586387039.1332022-06-012023-08-10
76992인천광역시중구281102022147012850310841인천광역시 중구 운서동 2850-3 1동 841호2931281058.922022-06-012023-08-10
42550인천광역시중구281102021118014933186[ 축항대로69번길 16 ] 0001동 0086호2543349022.02021-06-012023-08-10
1410인천광역시중구28110202114501195321507[ 은하수로29번길 47 ] 0001동 0507호3200197033.02021-06-012023-08-10
38117인천광역시중구281102021125013101인천광역시 중구 답동 3-1 1호41140000110.02021-06-012023-08-10
27745인천광역시중구281102021134012302612인천광역시 중구 경동 230-26 1동 2호8377308096.02021-06-012023-08-10
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
34340인천광역시중구2811020211180165421102[ 연안부두로115번길 25-8 ] 0001동 0102호3600676093.02021-06-012023-08-10
72158인천광역시중구2811020221490117921420001인천광역시 중구 을왕동 179-214 2동 1호120076800508.82022-06-012023-08-10
55725인천광역시중구281102022148014538190010000[ 백운로414번길 83-48 ] 9001동 0000호191520018.02022-06-012023-08-10
2003인천광역시중구2811020211450118861811924[ 자연대로 32 ] 0001동 1924호4357928039.02021-06-012023-08-10
37793인천광역시중구281102021123012511[ 우현로35번길 21 ] 0001동 0001호571200060.02021-06-012023-08-10
78293인천광역시중구281102022147012804310203[ 신도시남로142번길 17 ] 0001동 0203호82927890110.132022-06-012023-08-10
12465인천광역시중구281102021145011873811818[ 자연대로 29 ] 0001동 1818호4007685035.02021-06-012023-08-10
24360인천광역시중구281102021127015450202인천광역시 중구 신흥동2가 54-5 202호1281001.02021-06-012023-08-10
68383인천광역시중구281102022145011873811412[ 자연대로 29 ] 0001동 1412호4077388034.792022-06-012023-08-10
61986인천광역시중구281102022145011952401609[ 은하수로29번길 31 ] 0000동 1609호4305910040.35532022-06-012023-08-10

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일# duplicates
0인천광역시중구2811020211180182113인천광역시 중구 항동7가 82-1 1동 3호483000030.02021-06-012023-08-102
1인천광역시중구281102021127015450105인천광역시 중구 신흥동2가 54-5 105호1473101.02021-06-012023-08-102
2인천광역시중구281102021127015450111인천광역시 중구 신흥동2가 54-5 111호1473101.02021-06-012023-08-102
3인천광역시중구281102021127015450204인천광역시 중구 신흥동2가 54-5 204호1281001.02021-06-012023-08-102
4인천광역시중구28110202112801424411[ 축항대로296번길 60-39 ] 0001동 0001호102298140234.02021-06-012023-08-102
5인천광역시중구2811020211360124402[ 큰우물로 28-46 ] 0000동 0002호1112410056.02021-06-012023-08-102
6인천광역시중구281102021147012708211인천광역시 중구 운서동 2708-2 1동 1호11842526402049.02021-06-012023-08-102
7인천광역시중구281102021147012806310[ 영종대로 124 ] 0001동 0000호542790470812.02021-06-012023-08-102
8인천광역시중구281102021147012855012인천광역시 중구 운서동 2855 1동 2호199806040398.02021-06-012023-08-102
9인천광역시중구281102021147013243011인천광역시 중구 운서동 3243 1동 1호9982486801745.02021-06-012023-08-102