Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
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.
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 13 (0.1%) 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 (95.4%)Imbalance
시가표준액 is highly skewed (γ1 = 51.11894411)Skewed
연면적 is highly skewed (γ1 = 42.13489057)Skewed
부번 has 893 (8.9%) zerosZeros
동 has 2761 (27.6%) zerosZeros

Reproduction

Analysis started2024-03-18 03:33:15.007442
Analysis finished2024-03-18 03:33:20.111496
Duration5.1 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

2024-03-18T12:33:20.186563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:20.260070image/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

2024-03-18T12:33:20.359110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:20.445523image/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

2024-03-18T12:33:20.533856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:20.615128image/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
6436 
2022
3564 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 6436
64.4%
2022 3564
35.6%

Length

2024-03-18T12:33:20.691734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:20.784106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 6436
64.4%
2022 3564
35.6%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.3072
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:20.918691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile118
Q1131
median145
Q3147
95-th percentile149
Maximum152
Range51
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.403641
Coefficient of variation (CV)0.081859668
Kurtosis0.20567932
Mean139.3072
Median Absolute Deviation (MAD)2
Skewness-1.1910764
Sum1393072
Variance130.04303
MonotonicityNot monotonic
2024-03-18T12:33:21.043332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 2573
25.7%
145 2328
23.3%
118 1100
11.0%
128 623
 
6.2%
149 554
 
5.5%
148 338
 
3.4%
146 314
 
3.1%
138 237
 
2.4%
136 164
 
1.6%
152 130
 
1.3%
Other values (41) 1639
16.4%
ValueCountFrequency (%)
101 14
 
0.1%
102 14
 
0.1%
103 40
0.4%
104 39
0.4%
105 5
 
0.1%
106 11
 
0.1%
107 1
 
< 0.1%
108 2
 
< 0.1%
109 6
 
0.1%
110 12
 
0.1%
ValueCountFrequency (%)
152 130
 
1.3%
151 120
 
1.2%
150 122
 
1.2%
149 554
 
5.5%
148 338
 
3.4%
147 2573
25.7%
146 314
 
3.1%
145 2328
23.3%
144 32
 
0.3%
143 13
 
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

2024-03-18T12:33:21.144264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:21.214978image/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
9949 
2
 
51

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 9949
99.5%
2 51
 
0.5%

Length

2024-03-18T12:33:21.286180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:21.360404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9949
99.5%
2 51
 
0.5%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct899
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1305.3332
Minimum1
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:21.454126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q154
median1257
Q32789
95-th percentile3096
Maximum3243
Range3242
Interquartile range (IQR)2735

Descriptive statistics

Standard deviation1193.75
Coefficient of variation (CV)0.91451747
Kurtosis-1.558711
Mean1305.3332
Median Absolute Deviation (MAD)1206.5
Skewness0.22527973
Sum13053332
Variance1425039.1
MonotonicityNot monotonic
2024-03-18T12:33:21.576121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1886 546
 
5.5%
1873 537
 
5.4%
2850 474
 
4.7%
27 306
 
3.1%
3098 257
 
2.6%
49 229
 
2.3%
7 214
 
2.1%
2803 203
 
2.0%
2807 172
 
1.7%
1 151
 
1.5%
Other values (889) 6911
69.1%
ValueCountFrequency (%)
1 151
1.5%
2 89
0.9%
3 86
0.9%
4 89
0.9%
5 44
 
0.4%
6 74
 
0.7%
7 214
2.1%
8 27
 
0.3%
9 47
 
0.5%
10 63
 
0.6%
ValueCountFrequency (%)
3243 33
0.3%
3238 4
 
< 0.1%
3234 6
 
0.1%
3233 3
 
< 0.1%
3231 12
 
0.1%
3220 1
 
< 0.1%
3212 2
 
< 0.1%
3210 1
 
< 0.1%
3202 11
 
0.1%
3196 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct276
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.0888
Minimum0
Maximum580
Zeros893
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:21.696632image/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 deviation57.45924
Coefficient of variation (CV)2.4886196
Kurtosis25.328131
Mean23.0888
Median Absolute Deviation (MAD)4
Skewness4.6320406
Sum230888
Variance3301.5643
MonotonicityNot monotonic
2024-03-18T12:33:21.810864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1410
14.1%
4 905
 
9.0%
0 893
 
8.9%
2 865
 
8.6%
3 746
 
7.5%
5 537
 
5.4%
6 494
 
4.9%
7 440
 
4.4%
8 326
 
3.3%
20 188
 
1.9%
Other values (266) 3196
32.0%
ValueCountFrequency (%)
0 893
8.9%
1 1410
14.1%
2 865
8.6%
3 746
7.5%
4 905
9.0%
5 537
 
5.4%
6 494
 
4.9%
7 440
 
4.4%
8 326
 
3.3%
9 145
 
1.5%
ValueCountFrequency (%)
580 2
< 0.1%
577 4
< 0.1%
533 3
< 0.1%
532 1
 
< 0.1%
524 2
< 0.1%
497 2
< 0.1%
495 1
 
< 0.1%
475 1
 
< 0.1%
474 1
 
< 0.1%
468 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct127
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean807.764
Minimum0
Maximum9281
Zeros2761
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:21.954942image/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 deviation2559.6082
Coefficient of variation (CV)3.1687574
Kurtosis6.2624079
Mean807.764
Median Absolute Deviation (MAD)0
Skewness2.8727199
Sum8077640
Variance6551593.9
MonotonicityNot monotonic
2024-03-18T12:33:22.088780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5081
50.8%
0 2761
27.6%
9001 521
 
5.2%
2 513
 
5.1%
3 253
 
2.5%
9002 119
 
1.2%
4 107
 
1.1%
9003 54
 
0.5%
5 41
 
0.4%
8001 34
 
0.3%
Other values (117) 516
 
5.2%
ValueCountFrequency (%)
0 2761
27.6%
1 5081
50.8%
2 513
 
5.1%
3 253
 
2.5%
4 107
 
1.1%
5 41
 
0.4%
6 29
 
0.3%
7 19
 
0.2%
8 16
 
0.2%
9 15
 
0.1%
ValueCountFrequency (%)
9281 1
< 0.1%
9068 1
< 0.1%
9065 1
< 0.1%
9059 1
< 0.1%
9050 2
< 0.1%
9047 1
< 0.1%
9042 1
< 0.1%
9040 1
< 0.1%
9038 2
< 0.1%
9037 1
< 0.1%

호
Text

Distinct1461
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:33:22.420485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.8208
Min length1

Characters and Unicode

Total characters28208
Distinct characters17
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

Unique526 ?
Unique (%)5.3%

Sample

1st row0000
2nd row109
3rd row0520
4th row0002
5th row0805
ValueCountFrequency (%)
1 1336
 
13.3%
0001 692
 
6.9%
2 543
 
5.4%
3 362
 
3.6%
0 309
 
3.1%
4 222
 
2.2%
0000 179
 
1.8%
5 153
 
1.5%
0002 150
 
1.5%
101 140
 
1.4%
Other values (1454) 5930
59.2%
2024-03-18T12:33:22.969293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9390
33.3%
1 7119
25.2%
2 3112
 
11.0%
3 1921
 
6.8%
4 1508
 
5.3%
5 1181
 
4.2%
8 1045
 
3.7%
6 1040
 
3.7%
7 968
 
3.4%
9 788
 
2.8%
Other values (7) 136
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28072
99.5%
Dash Punctuation 80
 
0.3%
Other Letter 32
 
0.1%
Space Separator 16
 
0.1%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9390
33.4%
1 7119
25.4%
2 3112
 
11.1%
3 1921
 
6.8%
4 1508
 
5.4%
5 1181
 
4.2%
8 1045
 
3.7%
6 1040
 
3.7%
7 968
 
3.4%
9 788
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%
Other Letter
ValueCountFrequency (%)
월 16
50.0%
일 16
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28168
99.9%
Hangul 32
 
0.1%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9390
33.3%
1 7119
25.3%
2 3112
 
11.0%
3 1921
 
6.8%
4 1508
 
5.4%
5 1181
 
4.2%
8 1045
 
3.7%
6 1040
 
3.7%
7 968
 
3.4%
9 788
 
2.8%
Other values (2) 96
 
0.3%
Latin
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%
Hangul
ValueCountFrequency (%)
월 16
50.0%
일 16
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28176
99.9%
Hangul 32
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9390
33.3%
1 7119
25.3%
2 3112
 
11.0%
3 1921
 
6.8%
4 1508
 
5.4%
5 1181
 
4.2%
8 1045
 
3.7%
6 1040
 
3.7%
7 968
 
3.4%
9 788
 
2.8%
Other values (5) 104
 
0.4%
Hangul
ValueCountFrequency (%)
월 16
50.0%
일 16
50.0%

물건지
Text

Distinct9320
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:33:23.259729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length25.7107
Min length15

Characters and Unicode

Total characters257107
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

Unique8769 ?
Unique (%)87.7%

Sample

1st row[ 화랑목로100번길 55 ] 0000동 0000호
2nd row[ 축항대로87번길 11 ] 0001동 0109호
3rd row[ 영종대로162번길 26 ] 0001동 0520호
4th row[ 축항대로290번길 52 ] 0001동 0002호
5th row[ 영종대로 118 ] 0001동 0805호
ValueCountFrequency (%)
13582
22.9%
0001동 3673
 
6.2%
인천광역시 3209
 
5.4%
중구 3209
 
5.4%
0000동 2259
 
3.8%
1동 1408
 
2.4%
0001호 1032
 
1.7%
1호 996
 
1.7%
운서동 794
 
1.3%
영종대로 650
 
1.1%
Other values (3809) 28525
48.1%
2024-03-18T12:33:23.614102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49337
19.2%
0 39849
15.5%
1 20609
 
8.0%
동 12741
 
5.0%
호 9797
 
3.8%
2 9252
 
3.6%
[ 6791
 
2.6%
] 6791
 
2.6%
로 6729
 
2.6%
3 6508
 
2.5%
Other values (142) 88703
34.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103257
40.2%
Other Letter 86807
33.8%
Space Separator 49337
19.2%
Open Punctuation 6791
 
2.6%
Close Punctuation 6791
 
2.6%
Dash Punctuation 4116
 
1.6%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12741
 
14.7%
호 9797
 
11.3%
로 6729
 
7.8%
중 3704
 
4.3%
길 3701
 
4.3%
번 3619
 
4.2%
시 3541
 
4.1%
광 3390
 
3.9%
인 3371
 
3.9%
역 3219
 
3.7%
Other values (125) 32995
38.0%
Decimal Number
ValueCountFrequency (%)
0 39849
38.6%
1 20609
20.0%
2 9252
 
9.0%
3 6508
 
6.3%
4 4810
 
4.7%
9 4694
 
4.5%
5 4569
 
4.4%
6 4448
 
4.3%
7 4361
 
4.2%
8 4157
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%
Space Separator
ValueCountFrequency (%)
49337
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6791
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6791
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170292
66.2%
Hangul 86807
33.8%
Latin 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12741
 
14.7%
호 9797
 
11.3%
로 6729
 
7.8%
중 3704
 
4.3%
길 3701
 
4.3%
번 3619
 
4.2%
시 3541
 
4.1%
광 3390
 
3.9%
인 3371
 
3.9%
역 3219
 
3.7%
Other values (125) 32995
38.0%
Common
ValueCountFrequency (%)
49337
29.0%
0 39849
23.4%
1 20609
12.1%
2 9252
 
5.4%
[ 6791
 
4.0%
] 6791
 
4.0%
3 6508
 
3.8%
4 4810
 
2.8%
9 4694
 
2.8%
5 4569
 
2.7%
Other values (4) 17082
 
10.0%
Latin
ValueCountFrequency (%)
B 6
75.0%
T 1
 
12.5%
S 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170300
66.2%
Hangul 86807
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49337
29.0%
0 39849
23.4%
1 20609
12.1%
2 9252
 
5.4%
[ 6791
 
4.0%
] 6791
 
4.0%
3 6508
 
3.8%
4 4810
 
2.8%
9 4694
 
2.8%
5 4569
 
2.7%
Other values (7) 17090
 
10.0%
Hangul
ValueCountFrequency (%)
동 12741
 
14.7%
호 9797
 
11.3%
로 6729
 
7.8%
중 3704
 
4.3%
길 3701
 
4.3%
번 3619
 
4.2%
시 3541
 
4.1%
광 3390
 
3.9%
인 3371
 
3.9%
역 3219
 
3.7%
Other values (125) 32995
38.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6476
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3301417 × 108
Minimum21300
Maximum9.8421477 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:23.759113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21300
5-th percentile1140336
Q113254555
median41167355
Q372443698
95-th percentile3.0838822 × 108
Maximum9.8421477 × 1010
Range9.8421456 × 1010
Interquartile range (IQR)59189142

Descriptive statistics

Standard deviation1.5232722 × 109
Coefficient of variation (CV)11.451955
Kurtosis2974.8553
Mean1.3301417 × 108
Median Absolute Deviation (MAD)28816185
Skewness51.118944
Sum1.3301417 × 1012
Variance2.3203583 × 1018
MonotonicityNot monotonic
2024-03-18T12:33:24.170813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51253410 62
 
0.6%
49637720 59
 
0.6%
40577880 58
 
0.6%
43059100 53
 
0.5%
41891550 52
 
0.5%
40597430 51
 
0.5%
36003970 49
 
0.5%
37161120 44
 
0.4%
46017400 38
 
0.4%
45863870 36
 
0.4%
Other values (6466) 9498
95.0%
ValueCountFrequency (%)
21300 1
 
< 0.1%
26400 1
 
< 0.1%
28400 3
< 0.1%
32670 1
 
< 0.1%
38880 1
 
< 0.1%
39760 3
< 0.1%
42600 3
< 0.1%
43920 5
0.1%
45980 1
 
< 0.1%
47520 1
 
< 0.1%
ValueCountFrequency (%)
98421477300 1
< 0.1%
88310495790 1
< 0.1%
42645229400 1
< 0.1%
39957802830 1
< 0.1%
27053094680 1
< 0.1%
15389437440 1
< 0.1%
14570670740 1
< 0.1%
8716216320 1
< 0.1%
8453553760 1
< 0.1%
8279559680 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2333
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean222.65086
Minimum0
Maximum123583
Zeros36
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:24.289487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q136
median55.44
Q3115
95-th percentile541.145
Maximum123583
Range123583
Interquartile range (IQR)79

Descriptive statistics

Standard deviation1994.107
Coefficient of variation (CV)8.9562065
Kurtosis2150.1646
Mean222.65086
Median Absolute Deviation (MAD)28.44
Skewness42.134891
Sum2226508.6
Variance3976462.9
MonotonicityNot monotonic
2024-03-18T12:33:24.411597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 367
 
3.7%
36.0 166
 
1.7%
45.0 146
 
1.5%
27.0 137
 
1.4%
58.0 116
 
1.2%
39.0 109
 
1.1%
40.0 109
 
1.1%
33.0 109
 
1.1%
54.0 105
 
1.1%
35.0 103
 
1.0%
Other values (2323) 8533
85.3%
ValueCountFrequency (%)
0.0 36
0.4%
0.2 1
 
< 0.1%
0.25 1
 
< 0.1%
0.56 1
 
< 0.1%
0.7 3
 
< 0.1%
1.0 28
0.3%
1.95 1
 
< 0.1%
2.0 14
 
0.1%
2.1 1
 
< 0.1%
2.6 1
 
< 0.1%
ValueCountFrequency (%)
123583.0 1
< 0.1%
92278.0 1
< 0.1%
62429.0 1
< 0.1%
56478.0 1
< 0.1%
54188.0 1
< 0.1%
41753.0 1
< 0.1%
18125.0 1
< 0.1%
14388.84 1
< 0.1%
13022.19 1
< 0.1%
12375.0 1
< 0.1%

기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-06-01
6436 
2022-06-01
3564 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021-06-01 6436
64.4%
2022-06-01 3564
35.6%

Length

2024-03-18T12:33:24.513454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:24.590138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 6436
64.4%
2022-06-01 3564
35.6%

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

2024-03-18T12:33:24.678653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:24.795416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-10 10000
100.0%

Interactions

2024-03-18T12:33:19.191571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.397750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.875534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.347019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.897906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.688956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.276161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.492142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.951540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.426407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.988710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.774963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.357523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.578729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.025193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.511306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.070271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.857012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.455630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.653008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.103362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.605325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.163939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.945089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.541863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.720890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.179765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.700914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.257296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.024915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.635904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:16.796022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.263454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:17.804356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:18.336658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:19.106095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:33:24.861975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동특수지본번부번동시가표준액연면적기준일자
과세년도1.0000.4360.0000.4150.1340.0640.0000.0001.000
법정동0.4361.0000.0920.8500.4760.2410.0000.0000.436
특수지0.0000.0921.0000.1040.0000.2290.0000.0000.000
본번0.4150.8500.1041.0000.3520.3520.0000.0000.415
부번0.1340.4760.0000.3521.0000.0000.0000.0000.134
동0.0640.2410.2290.3520.0001.0000.0000.0000.064
시가표준액0.0000.0000.0000.0000.0000.0001.0000.9340.000
연면적0.0000.0000.0000.0000.0000.0000.9341.0000.000
기준일자1.0000.4360.0000.4150.1340.0640.0000.0001.000
2024-03-18T12:33:24.956764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자과세년도특수지
기준일자1.0001.0000.000
과세년도1.0001.0000.000
특수지0.0000.0001.000
2024-03-18T12:33:25.028718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적과세년도특수지기준일자
법정동1.0000.644-0.2740.1090.1410.0360.3350.0710.335
본번0.6441.000-0.346-0.1650.3340.0520.3190.0800.319
부번-0.274-0.3461.000-0.028-0.094-0.0680.1020.0000.102
동0.109-0.165-0.0281.000-0.248-0.0590.0780.2800.078
시가표준액0.1410.334-0.094-0.2481.0000.7620.0000.0000.000
연면적0.0360.052-0.068-0.0590.7621.0000.0000.0000.000
과세년도0.3350.3190.1020.0780.0000.0001.0000.0001.000
특수지0.0710.0800.0000.2800.0000.0000.0001.0000.000
기준일자0.3350.3190.1020.0780.0000.0001.0000.0001.000

Missing values

2024-03-18T12:33:19.785817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:33:19.969327image/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
60352인천광역시중구2811020221470130472600000[ 화랑목로100번길 55 ] 0000동 0000호146112440149.32022-06-012023-08-10
43509인천광역시중구2811020211180149341109[ 축항대로87번길 11 ] 0001동 0109호2116715018.02021-06-012023-08-10
59701인천광역시중구281102022147013090310520[ 영종대로162번길 26 ] 0001동 0520호5165600046.962022-06-012023-08-10
59408인천광역시중구28110202212801501010002[ 축항대로290번길 52 ] 0001동 0002호59287050129.932022-06-012023-08-10
78785인천광역시중구281102022147012806110805[ 영종대로 118 ] 0001동 0805호3022638048.912022-06-012023-08-10
6451인천광역시중구281102021147013098401508[ 영종대로196번길 15-30 ] 0000동 1508호4496160046.02021-06-012023-08-10
39561인천광역시중구2811020211180116111인천광역시 중구 항동7가 16-1 1동 1호46410022.02021-06-012023-08-10
28423인천광역시중구28110202113301113211[ 개항로 39 ] 0001동 0001호673219091.02021-06-012023-08-10
23630인천광역시중구2811020211270143314[ 서해대로449번길 10 ] 0001동 0004호51468300124.02021-06-012023-08-10
10212인천광역시중구28110202114901678581201[ 선녀바위로 43 ] 0001동 0201호154728000252.02021-06-012023-08-10
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
24601인천광역시중구281102021127015450216인천광역시 중구 신흥동2가 54-5 216호549000.02021-06-012023-08-10
27076인천광역시중구2811020211280173081719인천광역시 중구 신흥동3가 7-308 1동 719호2507841044.02021-06-012023-08-10
66791인천광역시중구281102022145011886700325[ 영종대로 911 ] 0000동 0325호4586387039.1332022-06-012023-08-10
50011인천광역시중구28110202114701285947101인천광역시 중구 운서동 2859-4 7동 101호1538943744054188.02021-06-012023-08-10
10929인천광역시중구2811020211480112615890022[ 백운로186번길 97-30 ] 9002동 0002호82800012.02021-06-012023-08-10
38516인천광역시중구2811020211230173312[ 제물량로 160 ] 0001동 0002호2313938075.02021-06-012023-08-10
39258인천광역시중구28110202111801273211163[ 연안부두로 27 ] 0001동 1163호597072018.02021-06-012023-08-10
73113인천광역시중구28110202214601588890030001인천광역시 중구 운남동 588-8 9003동 1호992807.32022-06-012023-08-10
67360인천광역시중구2811020221450118861811323[ 자연대로 32 ] 0001동 1323호4499012039.192022-06-012023-08-10
6805인천광역시중구281102021146011730590011인천광역시 중구 운남동 1730-5 9001동 1호313200018.02021-06-012023-08-10

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일# duplicates
7인천광역시중구2811020211470128510281101인천광역시 중구 운서동 2851 281동 101호1982880039.02021-06-012023-08-103
0인천광역시중구28110202111801822111인천광역시 중구 항동7가 82-21 1동 1호233057000488.02021-06-012023-08-102
1인천광역시중구28110202111801109111인천광역시 중구 항동7가 109-1 1동 1호97002720394.02021-06-012023-08-102
2인천광역시중구28110202112801391311[ 서해대로410번길 59-6 ] 0001동 0001호7723520090.02021-06-012023-08-102
3인천광역시중구28110202112801431211[ 축항대로296번길 56-20 ] 0001동 0001호87620830181.02021-06-012023-08-102
4인천광역시중구2811020211280171240인천광역시 중구 신흥동3가 71-2 4동202888800372.02021-06-012023-08-102
5인천광역시중구2811020211380136311인천광역시 중구 북성동1가 3-63 1동 1호293322700514.02021-06-012023-08-102
6인천광역시중구281102021146014351010[ 운중로14번길 12 ] 0001동 0000호1965120027.02021-06-012023-08-102
8인천광역시중구281102021147013243014인천광역시 중구 운서동 3243 1동 4호106347600155.02021-06-012023-08-102
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