Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows17
Duplicate rows (%)0.2%
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.
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 17 (0.2%) duplicate rowsDuplicates
기준일자 is highly overall correlated with 과세년도High correlation
과세년도 is highly overall correlated with 기준일자High 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 (95.6%)Imbalance
시가표준액 is highly skewed (γ1 = 53.51713839)Skewed
연면적 is highly skewed (γ1 = 35.09367077)Skewed
부번 has 824 (8.2%) zerosZeros
동 has 2751 (27.5%) zerosZeros

Reproduction

Analysis started2024-03-18 03:32:50.391957
Analysis finished2024-03-18 03:32:55.229848
Duration4.84 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

2024-03-18T12:32:55.280113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:55.350022image/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

2024-03-18T12:32:55.424446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:55.499103image/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

2024-03-18T12:32:55.570817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:55.642547image/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
6552 
2022
3448 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 6552
65.5%
2022 3448
34.5%

Length

2024-03-18T12:32:55.718102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:55.788450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 6552
65.5%
2022 3448
34.5%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.3996
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:55.883513image/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 deviation11.306428
Coefficient of variation (CV)0.081108034
Kurtosis0.24982444
Mean139.3996
Median Absolute Deviation (MAD)2
Skewness-1.2071749
Sum1393996
Variance127.8353
MonotonicityNot monotonic
2024-03-18T12:32:56.003171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 2580
25.8%
145 2389
23.9%
118 1094
10.9%
128 584
 
5.8%
149 538
 
5.4%
148 321
 
3.2%
146 275
 
2.8%
138 264
 
2.6%
136 160
 
1.6%
150 146
 
1.5%
Other values (42) 1649
16.5%
ValueCountFrequency (%)
101 14
 
0.1%
102 9
 
0.1%
103 46
0.5%
104 29
0.3%
105 4
 
< 0.1%
106 12
 
0.1%
107 2
 
< 0.1%
108 1
 
< 0.1%
109 9
 
0.1%
110 11
 
0.1%
ValueCountFrequency (%)
152 121
 
1.2%
151 126
 
1.3%
150 146
 
1.5%
149 538
 
5.4%
148 321
 
3.2%
147 2580
25.8%
146 275
 
2.8%
145 2389
23.9%
144 22
 
0.2%
143 12
 
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

2024-03-18T12:32:56.101841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:56.429441image/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
9952 
2
 
48

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 9952
99.5%
2 48
 
0.5%

Length

2024-03-18T12:32:56.503808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:56.591289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9952
99.5%
2 48
 
0.5%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct913
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1308.9107
Minimum1
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:56.675267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q156
median1272
Q32789
95-th percentile3096
Maximum3243
Range3242
Interquartile range (IQR)2733

Descriptive statistics

Standard deviation1191.0427
Coefficient of variation (CV)0.90994956
Kurtosis-1.5637482
Mean1308.9107
Median Absolute Deviation (MAD)1218
Skewness0.214046
Sum13089107
Variance1418582.8
MonotonicityNot monotonic
2024-03-18T12:32:56.875367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1873 554
 
5.5%
1886 523
 
5.2%
2850 463
 
4.6%
27 319
 
3.2%
3098 246
 
2.5%
2803 233
 
2.3%
7 217
 
2.2%
49 199
 
2.0%
1 168
 
1.7%
2807 162
 
1.6%
Other values (903) 6916
69.2%
ValueCountFrequency (%)
1 168
1.7%
2 92
0.9%
3 88
0.9%
4 92
0.9%
5 38
 
0.4%
6 102
1.0%
7 217
2.2%
8 20
 
0.2%
9 48
 
0.5%
10 53
 
0.5%
ValueCountFrequency (%)
3243 30
0.3%
3238 2
 
< 0.1%
3234 8
 
0.1%
3233 4
 
< 0.1%
3231 12
 
0.1%
3210 1
 
< 0.1%
3203 1
 
< 0.1%
3202 10
 
0.1%
3198 1
 
< 0.1%
3197 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct281
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.8129
Minimum0
Maximum607
Zeros824
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:57.010901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q317
95-th percentile121
Maximum607
Range607
Interquartile range (IQR)15

Descriptive statistics

Standard deviation56.036437
Coefficient of variation (CV)2.4563487
Kurtosis24.137722
Mean22.8129
Median Absolute Deviation (MAD)4
Skewness4.530415
Sum228129
Variance3140.0823
MonotonicityNot monotonic
2024-03-18T12:32:57.127100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1494
14.9%
2 906
 
9.1%
4 856
 
8.6%
0 824
 
8.2%
3 742
 
7.4%
5 541
 
5.4%
6 489
 
4.9%
7 428
 
4.3%
8 321
 
3.2%
20 189
 
1.9%
Other values (271) 3210
32.1%
ValueCountFrequency (%)
0 824
8.2%
1 1494
14.9%
2 906
9.1%
3 742
7.4%
4 856
8.6%
5 541
 
5.4%
6 489
 
4.9%
7 428
 
4.3%
8 321
 
3.2%
9 154
 
1.5%
ValueCountFrequency (%)
607 1
 
< 0.1%
577 1
 
< 0.1%
559 2
< 0.1%
539 1
 
< 0.1%
533 1
 
< 0.1%
524 3
< 0.1%
516 1
 
< 0.1%
500 1
 
< 0.1%
494 2
< 0.1%
468 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct123
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean804.8393
Minimum0
Maximum9066
Zeros2751
Zeros (%)27.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:57.245868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile9001
Maximum9066
Range9066
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2555.2328
Coefficient of variation (CV)3.1748361
Kurtosis6.2927097
Mean804.8393
Median Absolute Deviation (MAD)0
Skewness2.877846
Sum8048393
Variance6529214.8
MonotonicityNot monotonic
2024-03-18T12:32:57.344649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5101
51.0%
0 2751
27.5%
2 535
 
5.3%
9001 529
 
5.3%
3 237
 
2.4%
9002 128
 
1.3%
4 107
 
1.1%
5 53
 
0.5%
9003 49
 
0.5%
8001 34
 
0.3%
Other values (113) 476
 
4.8%
ValueCountFrequency (%)
0 2751
27.5%
1 5101
51.0%
2 535
 
5.3%
3 237
 
2.4%
4 107
 
1.1%
5 53
 
0.5%
6 21
 
0.2%
7 28
 
0.3%
8 9
 
0.1%
9 12
 
0.1%
ValueCountFrequency (%)
9066 1
 
< 0.1%
9063 1
 
< 0.1%
9055 1
 
< 0.1%
9054 1
 
< 0.1%
9053 1
 
< 0.1%
9050 2
 
< 0.1%
9041 1
 
< 0.1%
9032 1
 
< 0.1%
9031 2
 
< 0.1%
9029 6
0.1%

호
Text

Distinct1477
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:32:57.627697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length2.7968
Min length1

Characters and Unicode

Total characters27968
Distinct characters19
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

Unique537 ?
Unique (%)5.4%

Sample

1st row0910
2nd row101
3rd row401
4th row1
5th row1
ValueCountFrequency (%)
1 1417
 
14.2%
0001 585
 
5.8%
2 526
 
5.3%
3 344
 
3.4%
0 317
 
3.2%
4 231
 
2.3%
0000 169
 
1.7%
5 155
 
1.5%
0002 147
 
1.5%
101 137
 
1.4%
Other values (1471) 5984
59.8%
2024-03-18T12:32:58.029804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9124
32.6%
1 7126
25.5%
2 3167
 
11.3%
3 1880
 
6.7%
4 1510
 
5.4%
5 1230
 
4.4%
8 1048
 
3.7%
6 1022
 
3.7%
7 910
 
3.3%
9 812
 
2.9%
Other values (9) 139
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27829
99.5%
Dash Punctuation 84
 
0.3%
Other Letter 26
 
0.1%
Uppercase Letter 17
 
0.1%
Space Separator 12
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9124
32.8%
1 7126
25.6%
2 3167
 
11.4%
3 1880
 
6.8%
4 1510
 
5.4%
5 1230
 
4.4%
8 1048
 
3.8%
6 1022
 
3.7%
7 910
 
3.3%
9 812
 
2.9%
Other Letter
ValueCountFrequency (%)
월 12
46.2%
일 12
46.2%
지 1
 
3.8%
비 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 8
47.1%
T 5
29.4%
S 4
23.5%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27925
99.8%
Hangul 26
 
0.1%
Latin 17
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9124
32.7%
1 7126
25.5%
2 3167
 
11.3%
3 1880
 
6.7%
4 1510
 
5.4%
5 1230
 
4.4%
8 1048
 
3.8%
6 1022
 
3.7%
7 910
 
3.3%
9 812
 
2.9%
Other values (2) 96
 
0.3%
Hangul
ValueCountFrequency (%)
월 12
46.2%
일 12
46.2%
지 1
 
3.8%
비 1
 
3.8%
Latin
ValueCountFrequency (%)
B 8
47.1%
T 5
29.4%
S 4
23.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27942
99.9%
Hangul 26
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9124
32.7%
1 7126
25.5%
2 3167
 
11.3%
3 1880
 
6.7%
4 1510
 
5.4%
5 1230
 
4.4%
8 1048
 
3.8%
6 1022
 
3.7%
7 910
 
3.3%
9 812
 
2.9%
Other values (5) 113
 
0.4%
Hangul
ValueCountFrequency (%)
월 12
46.2%
일 12
46.2%
지 1
 
3.8%
비 1
 
3.8%

물건지
Text

Distinct9343
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:32:58.261121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length25.6777
Min length16

Characters and Unicode

Total characters256777
Distinct characters152
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

Unique8796 ?
Unique (%)88.0%

Sample

1st row[ 영종대로 100 ] 0001동 0910호
2nd row인천광역시 중구 운서동 2851-54 6동 101호
3rd row[ 흰바위로59번길 8 ] 0003동 0401호
4th row인천광역시 중구 항동7가 112 7동 1호
5th row[ 자유공원로 15 ] 0002동 0001호
ValueCountFrequency (%)
13666
23.0%
0001동 3733
 
6.3%
중구 3167
 
5.3%
인천광역시 3167
 
5.3%
0000동 2223
 
3.7%
1동 1368
 
2.3%
0001호 1003
 
1.7%
1호 998
 
1.7%
운서동 787
 
1.3%
영종대로 636
 
1.1%
Other values (3853) 28565
48.2%
2024-03-18T12:32:58.627916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49313
19.2%
0 39873
15.5%
1 20561
 
8.0%
동 12674
 
4.9%
호 9799
 
3.8%
2 9373
 
3.7%
[ 6833
 
2.7%
] 6833
 
2.7%
로 6765
 
2.6%
3 6376
 
2.5%
Other values (142) 88377
34.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103202
40.2%
Other Letter 86495
33.7%
Space Separator 49313
19.2%
Open Punctuation 6833
 
2.7%
Close Punctuation 6833
 
2.7%
Dash Punctuation 4084
 
1.6%
Uppercase Letter 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12674
 
14.7%
호 9799
 
11.3%
로 6765
 
7.8%
중 3706
 
4.3%
길 3665
 
4.2%
번 3584
 
4.1%
시 3554
 
4.1%
광 3349
 
3.9%
인 3347
 
3.9%
역 3179
 
3.7%
Other values (125) 32873
38.0%
Decimal Number
ValueCountFrequency (%)
0 39873
38.6%
1 20561
19.9%
2 9373
 
9.1%
3 6376
 
6.2%
4 4900
 
4.7%
9 4737
 
4.6%
5 4633
 
4.5%
6 4368
 
4.2%
7 4232
 
4.1%
8 4149
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
47.1%
T 5
29.4%
S 4
23.5%
Space Separator
ValueCountFrequency (%)
49313
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6833
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6833
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4084
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170265
66.3%
Hangul 86495
33.7%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12674
 
14.7%
호 9799
 
11.3%
로 6765
 
7.8%
중 3706
 
4.3%
길 3665
 
4.2%
번 3584
 
4.1%
시 3554
 
4.1%
광 3349
 
3.9%
인 3347
 
3.9%
역 3179
 
3.7%
Other values (125) 32873
38.0%
Common
ValueCountFrequency (%)
49313
29.0%
0 39873
23.4%
1 20561
12.1%
2 9373
 
5.5%
[ 6833
 
4.0%
] 6833
 
4.0%
3 6376
 
3.7%
4 4900
 
2.9%
9 4737
 
2.8%
5 4633
 
2.7%
Other values (4) 16833
 
9.9%
Latin
ValueCountFrequency (%)
B 8
47.1%
T 5
29.4%
S 4
23.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170282
66.3%
Hangul 86495
33.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49313
29.0%
0 39873
23.4%
1 20561
12.1%
2 9373
 
5.5%
[ 6833
 
4.0%
] 6833
 
4.0%
3 6376
 
3.7%
4 4900
 
2.9%
9 4737
 
2.8%
5 4633
 
2.7%
Other values (7) 16850
 
9.9%
Hangul
ValueCountFrequency (%)
동 12674
 
14.7%
호 9799
 
11.3%
로 6765
 
7.8%
중 3706
 
4.3%
길 3665
 
4.2%
번 3584
 
4.1%
시 3554
 
4.1%
광 3349
 
3.9%
인 3347
 
3.9%
역 3179
 
3.7%
Other values (125) 32873
38.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6488
Distinct (%)64.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4650922 × 108
Minimum28400
Maximum1.22466 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:58.756912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28400
5-th percentile1137600
Q112936780
median41147630
Q373456405
95-th percentile3.050866 × 108
Maximum1.22466 × 1011
Range1.2246597 × 1011
Interquartile range (IQR)60519625

Descriptive statistics

Standard deviation1.5779775 × 109
Coefficient of variation (CV)10.7705
Kurtosis3758.2487
Mean1.4650922 × 108
Median Absolute Deviation (MAD)29854620
Skewness53.517138
Sum1.4650922 × 1012
Variance2.4900131 × 1018
MonotonicityNot monotonic
2024-03-18T12:32:58.875124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41891550 65
 
0.7%
40577880 55
 
0.5%
49637720 52
 
0.5%
43059100 51
 
0.5%
40597430 51
 
0.5%
36003970 50
 
0.5%
51253410 46
 
0.5%
40345880 42
 
0.4%
37161120 40
 
0.4%
46017400 40
 
0.4%
Other values (6478) 9508
95.1%
ValueCountFrequency (%)
28400 2
 
< 0.1%
31460 1
 
< 0.1%
35100 1
 
< 0.1%
36300 1
 
< 0.1%
39600 1
 
< 0.1%
39760 2
 
< 0.1%
42600 4
< 0.1%
43920 5
0.1%
49500 1
 
< 0.1%
50160 1
 
< 0.1%
ValueCountFrequency (%)
122466000000 1
< 0.1%
42645229400 1
< 0.1%
39449487950 1
< 0.1%
35920710000 1
< 0.1%
28521529880 1
< 0.1%
25851259280 1
< 0.1%
22450652280 1
< 0.1%
18859696240 1
< 0.1%
18726420410 1
< 0.1%
17669430410 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2352
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247.51457
Minimum0
Maximum127968
Zeros35
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:32:59.011956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q136
median55.5
Q3115.4025
95-th percentile531.905
Maximum127968
Range127968
Interquartile range (IQR)79.4025

Descriptive statistics

Standard deviation2186.5331
Coefficient of variation (CV)8.833957
Kurtosis1588.5404
Mean247.51457
Median Absolute Deviation (MAD)28.452
Skewness35.093671
Sum2475145.7
Variance4780926.9
MonotonicityNot monotonic
2024-03-18T12:32:59.153114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 374
 
3.7%
36.0 165
 
1.7%
45.0 139
 
1.4%
40.0 119
 
1.2%
27.0 113
 
1.1%
35.0 107
 
1.1%
42.0 103
 
1.0%
58.0 98
 
1.0%
49.0 94
 
0.9%
33.0 94
 
0.9%
Other values (2342) 8594
85.9%
ValueCountFrequency (%)
0.0 35
0.4%
0.3 1
 
< 0.1%
0.38 1
 
< 0.1%
0.41 1
 
< 0.1%
0.43 1
 
< 0.1%
0.7 2
 
< 0.1%
0.9 1
 
< 0.1%
1.0 33
0.3%
1.9 1
 
< 0.1%
2.0 10
 
0.1%
ValueCountFrequency (%)
127968.0 1
< 0.1%
80903.0 1
< 0.1%
62429.0 1
< 0.1%
60501.0 1
< 0.1%
56478.277 1
< 0.1%
54188.0 1
< 0.1%
41966.0 1
< 0.1%
39089.0 1
< 0.1%
34619.0 1
< 0.1%
30616.0 1
< 0.1%

기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-06-01
6552 
2022-06-01
3448 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-06-01 6552
65.5%
2022-06-01 3448
34.5%

Length

2024-03-18T12:32:59.259798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:59.335353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 6552
65.5%
2022-06-01 3448
34.5%

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

2024-03-18T12:32:59.414373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:32:59.498697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-10 10000
100.0%

Interactions

2024-03-18T12:32:54.385996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:51.798482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.267138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.805811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.298440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.748989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.464188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:51.865726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.344941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.895951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.374807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.853662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.562086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:51.937809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.461601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.979289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.443393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.948468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.687480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.027898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.547456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.066462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.516138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.041001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.786617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.113215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.632187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.145068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.578783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.171653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.874121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.191354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:52.719710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.223469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:53.652594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:32:54.303033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:32:59.558826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동특수지본번부번동시가표준액연면적기준일자
과세년도1.0000.4420.0000.4330.1190.0370.0070.0001.000
법정동0.4421.0000.0840.8520.4680.2360.0000.0000.442
특수지0.0000.0841.0000.1000.0000.2110.0000.0000.000
본번0.4330.8520.1001.0000.3410.3620.0870.0760.433
부번0.1190.4680.0000.3411.0000.0000.0000.0000.119
동0.0370.2360.2110.3620.0001.0000.0000.0000.037
시가표준액0.0070.0000.0000.0870.0000.0001.0000.8780.007
연면적0.0000.0000.0000.0760.0000.0000.8781.0000.000
기준일자1.0000.4420.0000.4330.1190.0370.0070.0001.000
2024-03-18T12:32:59.669531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자과세년도특수지
기준일자1.0001.0000.000
과세년도1.0001.0000.000
특수지0.0000.0001.000
2024-03-18T12:32:59.749706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적과세년도특수지기준일자
법정동1.0000.645-0.2900.1240.1430.0320.3400.0650.340
본번0.6451.000-0.344-0.1470.3310.0510.3330.0760.333
부번-0.290-0.3441.000-0.029-0.092-0.0560.0910.0000.091
동0.124-0.147-0.0291.000-0.236-0.0700.0450.2570.045
시가표준액0.1430.331-0.092-0.2361.0000.7720.0090.0000.009
연면적0.0320.051-0.056-0.0700.7721.0000.0000.0000.000
과세년도0.3400.3330.0910.0450.0090.0001.0000.0001.000
특수지0.0650.0760.0000.2570.0000.0000.0001.0000.000
기준일자0.3400.3330.0910.0450.0090.0001.0000.0001.000

Missing values

2024-03-18T12:32:54.994652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:32:55.153383image/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
80354인천광역시중구281102022147012799210910[ 영종대로 100 ] 0001동 0910호3240953053.982022-06-012023-08-10
50576인천광역시중구281102021147012851546101인천광역시 중구 운서동 2851-54 6동 101호12316003.02021-06-012023-08-10
19847인천광역시중구28110202114701280743401[ 흰바위로59번길 8 ] 0003동 0401호6099048058.02021-06-012023-08-10
38254인천광역시중구28110202111801112071인천광역시 중구 항동7가 112 7동 1호173365920374.02021-06-012023-08-10
49983인천광역시중구2811020211360117321[ 자유공원로 15 ] 0002동 0001호168448011.02021-06-012023-08-10
27854인천광역시중구28110202113801611914인천광역시 중구 북성동1가 6-119 1동 4호259200054.02021-06-012023-08-10
33895인천광역시중구28110202111801278922[ 연안부두로33번길 1 ] 0002동 0002호679296037.02021-06-012023-08-10
1455인천광역시중구281102021145011886402007[ 하늘별빛로65번길 7-11 ] 0000동 2007호4963772045.02021-06-012023-08-10
33976인천광역시중구2811020211180133011인천광역시 중구 항동7가 33 1동 1호8340802.02021-06-012023-08-10
68553인천광역시중구281102022145011873501113[ 자연대로 41 ] 0000동 1113호3716112033.06152022-06-012023-08-10
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
26337인천광역시중구28110202112801721516인천광역시 중구 신흥동3가 7-215 1동 6호626544017.02021-06-012023-08-10
29299인천광역시중구2811020211360110024인천광역시 중구 인현동 1 24호531301.02021-06-012023-08-10
24885인천광역시중구28110202112801731890011[ 인항로 39 ] 9001동 0001호49725000221.02021-06-012023-08-10
69772인천광역시중구281102022145011883810003[ 하늘중앙로195번길 29 ] 0001동 0003호8361661601577.6722022-06-012023-08-10
27858인천광역시중구28110202113801614916인천광역시 중구 북성동1가 6-149 1동 6호40884800162.02021-06-012023-08-10
43632인천광역시중구28110202112801712113인천광역시 중구 신흥동3가 7-121 1동 3호53240000440.02021-06-012023-08-10
3677인천광역시중구281102021145011886701515[ 영종대로 911 ] 0000동 1515호4328109039.02021-06-012023-08-10
23820인천광역시중구2811020211300122612인천광역시 중구 유동 22-6 1동 2호2146560083.02021-06-012023-08-10
23097인천광역시중구28110202114701279921204[ 영종대로 100 ] 0001동 0204호152090910240.02021-06-012023-08-10
20879인천광역시중구281102021147012850601004인천광역시 중구 운서동 2850-6 1004호3391328065.02021-06-012023-08-10

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일# duplicates
13인천광역시중구2811020211490176210011[ 용유서로348번길 16 ] 0001동 0001호80186400117.02021-06-012023-08-103
0인천광역시중구2811020211180127451인천광역시 중구 항동7가 27-4 5동 1호298800018.02021-06-012023-08-102
1인천광역시중구281102021118012769293인천광역시 중구 항동7가 27-69 2동 93호292581017.02021-06-012023-08-102
2인천광역시중구2811020211180182113인천광역시 중구 항동7가 82-1 1동 3호708000030.02021-06-012023-08-102
3인천광역시중구281102021127015450110인천광역시 중구 신흥동2가 54-5 110호1473101.02021-06-012023-08-102
4인천광역시중구281102021127015450120인천광역시 중구 신흥동2가 54-5 120호1473101.02021-06-012023-08-102
5인천광역시중구28110202112801424312[ 축항대로296번길 60-28 ] 0001동 0002호3273750075.02021-06-012023-08-102
6인천광역시중구2811020211280172000인천광역시 중구 신흥동3가 7242336670122.02021-06-012023-08-102
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