Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows16
Duplicate rows (%)0.2%
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 16 (0.2%) 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 (95.4%)Imbalance
시가표준액 is highly skewed (γ1 = 45.6695628)Skewed
연면적 is highly skewed (γ1 = 37.67615795)Skewed
부번 has 875 (8.8%) zerosZeros
동 has 2782 (27.8%) zerosZeros

Reproduction

Analysis started2024-03-18 03:33:02.357276
Analysis finished2024-03-18 03:33:07.276257
Duration4.92 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

2024-03-18T12:33:07.338089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:07.442556image/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

2024-03-18T12:33:07.526466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:07.646254image/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

2024-03-18T12:33:07.781291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:07.889272image/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
6565 
2022
3435 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 6565
65.6%
2022 3435
34.4%

Length

2024-03-18T12:33:07.977560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:08.053052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 6565
65.6%
2022 3435
34.4%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.4091
Minimum101
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:08.139844image/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 deviation11.333242
Coefficient of variation (CV)0.081294853
Kurtosis0.27294028
Mean139.4091
Median Absolute Deviation (MAD)2
Skewness-1.2175741
Sum1394091
Variance128.44238
MonotonicityNot monotonic
2024-03-18T12:33:08.253613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
147 2648
26.5%
145 2343
23.4%
118 1083
10.8%
128 578
 
5.8%
149 535
 
5.3%
148 317
 
3.2%
146 306
 
3.1%
138 263
 
2.6%
150 143
 
1.4%
136 141
 
1.4%
Other values (42) 1643
16.4%
ValueCountFrequency (%)
101 5
 
0.1%
102 13
 
0.1%
103 59
0.6%
104 34
0.3%
105 2
 
< 0.1%
106 4
 
< 0.1%
107 7
 
0.1%
108 1
 
< 0.1%
109 7
 
0.1%
110 5
 
0.1%
ValueCountFrequency (%)
152 119
 
1.2%
151 107
 
1.1%
150 143
 
1.4%
149 535
 
5.3%
148 317
 
3.2%
147 2648
26.5%
146 306
 
3.1%
145 2343
23.4%
144 24
 
0.2%
143 23
 
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

2024-03-18T12:33:08.354000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:08.423534image/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

2024-03-18T12:33:08.502341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:33:08.586343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9949
99.5%
2 51
 
0.5%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct884
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1320.1136
Minimum1
Maximum3243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:08.687450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q158
median1366
Q32793
95-th percentile3096
Maximum3243
Range3242
Interquartile range (IQR)2735

Descriptive statistics

Standard deviation1195.6674
Coefficient of variation (CV)0.9057307
Kurtosis-1.5796371
Mean1320.1136
Median Absolute Deviation (MAD)1313
Skewness0.19795217
Sum13201136
Variance1429620.6
MonotonicityNot monotonic
2024-03-18T12:33:08.797437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1873 560
 
5.6%
1886 530
 
5.3%
2850 464
 
4.6%
27 307
 
3.1%
3098 251
 
2.5%
7 224
 
2.2%
2803 221
 
2.2%
2807 195
 
1.9%
49 187
 
1.9%
1 166
 
1.7%
Other values (874) 6895
69.0%
ValueCountFrequency (%)
1 166
1.7%
2 96
1.0%
3 77
 
0.8%
4 84
 
0.8%
5 43
 
0.4%
6 96
1.0%
7 224
2.2%
8 20
 
0.2%
9 37
 
0.4%
10 60
 
0.6%
ValueCountFrequency (%)
3243 29
0.3%
3238 3
 
< 0.1%
3234 4
 
< 0.1%
3231 12
0.1%
3203 1
 
< 0.1%
3202 8
 
0.1%
3194 2
 
< 0.1%
3174 1
 
< 0.1%
3173 7
 
0.1%
3172 4
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct275
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.4912
Minimum0
Maximum580
Zeros875
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:08.929253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q317
95-th percentile112
Maximum580
Range580
Interquartile range (IQR)15

Descriptive statistics

Standard deviation57.504701
Coefficient of variation (CV)2.5567645
Kurtosis27.976124
Mean22.4912
Median Absolute Deviation (MAD)4
Skewness4.8570347
Sum224912
Variance3306.7906
MonotonicityNot monotonic
2024-03-18T12:33:09.059208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1490
14.9%
2 944
 
9.4%
4 891
 
8.9%
0 875
 
8.8%
3 707
 
7.1%
5 511
 
5.1%
6 494
 
4.9%
7 434
 
4.3%
8 344
 
3.4%
20 187
 
1.9%
Other values (265) 3123
31.2%
ValueCountFrequency (%)
0 875
8.8%
1 1490
14.9%
2 944
9.4%
3 707
7.1%
4 891
8.9%
5 511
 
5.1%
6 494
 
4.9%
7 434
 
4.3%
8 344
 
3.4%
9 161
 
1.6%
ValueCountFrequency (%)
580 2
 
< 0.1%
577 6
0.1%
541 1
 
< 0.1%
538 1
 
< 0.1%
533 2
 
< 0.1%
532 1
 
< 0.1%
525 3
< 0.1%
524 1
 
< 0.1%
497 1
 
< 0.1%
490 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct110
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean828.3385
Minimum0
Maximum9051
Zeros2782
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:09.177097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile9001
Maximum9051
Range9051
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2591.6878
Coefficient of variation (CV)3.1287786
Kurtosis5.9894033
Mean828.3385
Median Absolute Deviation (MAD)0
Skewness2.8252834
Sum8283385
Variance6716845.7
MonotonicityNot monotonic
2024-03-18T12:33:09.655435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 5060
50.6%
0 2782
27.8%
9001 527
 
5.3%
2 501
 
5.0%
3 271
 
2.7%
9002 127
 
1.3%
4 127
 
1.3%
9003 64
 
0.6%
5 52
 
0.5%
9004 43
 
0.4%
Other values (100) 446
 
4.5%
ValueCountFrequency (%)
0 2782
27.8%
1 5060
50.6%
2 501
 
5.0%
3 271
 
2.7%
4 127
 
1.3%
5 52
 
0.5%
6 30
 
0.3%
7 25
 
0.2%
8 15
 
0.1%
9 7
 
0.1%
ValueCountFrequency (%)
9051 1
< 0.1%
9050 2
< 0.1%
9044 1
< 0.1%
9040 1
< 0.1%
9039 2
< 0.1%
9036 1
< 0.1%
9034 1
< 0.1%
9031 1
< 0.1%
9030 1
< 0.1%
9028 1
< 0.1%

호
Text

Distinct1472
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:33:09.979983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length2.7889
Min length1

Characters and Unicode

Total characters27889
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

Unique498 ?
Unique (%)5.0%

Sample

1st row6
2nd row418
3rd row2
4th row0000
5th row1
ValueCountFrequency (%)
1 1405
 
14.0%
0001 606
 
6.1%
2 553
 
5.5%
3 348
 
3.5%
0 338
 
3.4%
4 241
 
2.4%
0000 173
 
1.7%
5 145
 
1.4%
0002 136
 
1.4%
101 130
 
1.3%
Other values (1464) 5940
59.3%
2024-03-18T12:33:10.400509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8908
31.9%
1 7165
25.7%
2 3208
 
11.5%
3 1901
 
6.8%
4 1477
 
5.3%
5 1175
 
4.2%
6 1049
 
3.8%
8 1029
 
3.7%
7 980
 
3.5%
9 854
 
3.1%
Other values (9) 143
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27746
99.5%
Dash Punctuation 81
 
0.3%
Other Letter 31
 
0.1%
Uppercase Letter 16
 
0.1%
Space Separator 15
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8908
32.1%
1 7165
25.8%
2 3208
 
11.6%
3 1901
 
6.9%
4 1477
 
5.3%
5 1175
 
4.2%
6 1049
 
3.8%
8 1029
 
3.7%
7 980
 
3.5%
9 854
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 10
62.5%
T 4
 
25.0%
S 1
 
6.2%
A 1
 
6.2%
Other Letter
ValueCountFrequency (%)
월 15
48.4%
일 15
48.4%
지 1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27842
99.8%
Hangul 31
 
0.1%
Latin 16
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8908
32.0%
1 7165
25.7%
2 3208
 
11.5%
3 1901
 
6.8%
4 1477
 
5.3%
5 1175
 
4.2%
6 1049
 
3.8%
8 1029
 
3.7%
7 980
 
3.5%
9 854
 
3.1%
Other values (2) 96
 
0.3%
Latin
ValueCountFrequency (%)
B 10
62.5%
T 4
 
25.0%
S 1
 
6.2%
A 1
 
6.2%
Hangul
ValueCountFrequency (%)
월 15
48.4%
일 15
48.4%
지 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27858
99.9%
Hangul 31
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8908
32.0%
1 7165
25.7%
2 3208
 
11.5%
3 1901
 
6.8%
4 1477
 
5.3%
5 1175
 
4.2%
6 1049
 
3.8%
8 1029
 
3.7%
7 980
 
3.5%
9 854
 
3.1%
Other values (6) 112
 
0.4%
Hangul
ValueCountFrequency (%)
월 15
48.4%
일 15
48.4%
지 1
 
3.2%

물건지
Text

Distinct9332
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-18T12:33:10.664941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length25.6887
Min length16

Characters and Unicode

Total characters256887
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

Unique8778 ?
Unique (%)87.8%

Sample

1st row[ 서해대로449번길 10 ] 0001동 0006호
2nd row[ 흰바위로59번길 8 ] 0002동 0418호
3rd row인천광역시 중구 운서동 2855 5동 2호
4th row인천광역시 중구 운북동 752-23 9001동
5th row인천광역시 중구 신흥동3가 31-7 8동 1호
ValueCountFrequency (%)
13732
23.1%
0001동 3692
 
6.2%
중구 3134
 
5.3%
인천광역시 3134
 
5.3%
0000동 2293
 
3.9%
1동 1368
 
2.3%
0001호 1019
 
1.7%
1호 991
 
1.7%
운서동 781
 
1.3%
영종대로 680
 
1.1%
Other values (3785) 28537
48.1%
2024-03-18T12:33:11.045068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49361
19.2%
0 40102
15.6%
1 20580
 
8.0%
동 12675
 
4.9%
호 9804
 
3.8%
2 9371
 
3.6%
] 6866
 
2.7%
[ 6866
 
2.7%
로 6814
 
2.7%
3 6440
 
2.5%
Other values (147) 88008
34.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103459
40.3%
Other Letter 86305
33.6%
Space Separator 49361
19.2%
Close Punctuation 6866
 
2.7%
Open Punctuation 6866
 
2.7%
Dash Punctuation 4014
 
1.6%
Uppercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12675
 
14.7%
호 9804
 
11.4%
로 6814
 
7.9%
길 3673
 
4.3%
중 3661
 
4.2%
번 3605
 
4.2%
시 3517
 
4.1%
광 3314
 
3.8%
인 3308
 
3.8%
역 3145
 
3.6%
Other values (129) 32789
38.0%
Decimal Number
ValueCountFrequency (%)
0 40102
38.8%
1 20580
19.9%
2 9371
 
9.1%
3 6440
 
6.2%
9 4848
 
4.7%
4 4803
 
4.6%
5 4440
 
4.3%
6 4374
 
4.2%
7 4299
 
4.2%
8 4202
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 10
62.5%
T 4
 
25.0%
S 1
 
6.2%
A 1
 
6.2%
Space Separator
ValueCountFrequency (%)
49361
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6866
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6866
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4014
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170566
66.4%
Hangul 86305
33.6%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12675
 
14.7%
호 9804
 
11.4%
로 6814
 
7.9%
길 3673
 
4.3%
중 3661
 
4.2%
번 3605
 
4.2%
시 3517
 
4.1%
광 3314
 
3.8%
인 3308
 
3.8%
역 3145
 
3.6%
Other values (129) 32789
38.0%
Common
ValueCountFrequency (%)
49361
28.9%
0 40102
23.5%
1 20580
12.1%
2 9371
 
5.5%
] 6866
 
4.0%
[ 6866
 
4.0%
3 6440
 
3.8%
9 4848
 
2.8%
4 4803
 
2.8%
5 4440
 
2.6%
Other values (4) 16889
 
9.9%
Latin
ValueCountFrequency (%)
B 10
62.5%
T 4
 
25.0%
S 1
 
6.2%
A 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170582
66.4%
Hangul 86305
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49361
28.9%
0 40102
23.5%
1 20580
12.1%
2 9371
 
5.5%
] 6866
 
4.0%
[ 6866
 
4.0%
3 6440
 
3.8%
9 4848
 
2.8%
4 4803
 
2.8%
5 4440
 
2.6%
Other values (8) 16905
 
9.9%
Hangul
ValueCountFrequency (%)
동 12675
 
14.7%
호 9804
 
11.4%
로 6814
 
7.9%
길 3673
 
4.3%
중 3661
 
4.2%
번 3605
 
4.2%
시 3517
 
4.1%
광 3314
 
3.8%
인 3308
 
3.8%
역 3145
 
3.6%
Other values (129) 32789
38.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6461
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3928268 × 108
Minimum21300
Maximum9.8421477 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:11.176574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21300
5-th percentile1123140
Q111630565
median40932160
Q370355165
95-th percentile3.0154595 × 108
Maximum9.8421477 × 1010
Range9.8421456 × 1010
Interquartile range (IQR)58724600

Descriptive statistics

Standard deviation1.4731699 × 109
Coefficient of variation (CV)10.576835
Kurtosis2568.4954
Mean1.3928268 × 108
Median Absolute Deviation (MAD)29315525
Skewness45.669563
Sum1.3928268 × 1012
Variance2.1702294 × 1018
MonotonicityNot monotonic
2024-03-18T12:33:11.295159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41891550 64
 
0.6%
49637720 64
 
0.6%
40577880 61
 
0.6%
51253410 56
 
0.6%
43059100 53
 
0.5%
36003970 50
 
0.5%
40597430 43
 
0.4%
46017400 42
 
0.4%
39080680 42
 
0.4%
45863870 37
 
0.4%
Other values (6451) 9488
94.9%
ValueCountFrequency (%)
21300 1
 
< 0.1%
28400 1
 
< 0.1%
39600 1
 
< 0.1%
39760 2
< 0.1%
42600 2
< 0.1%
43920 4
< 0.1%
47520 1
 
< 0.1%
48000 1
 
< 0.1%
49500 1
 
< 0.1%
53130 1
 
< 0.1%
ValueCountFrequency (%)
98421477300 1
< 0.1%
66515933260 1
< 0.1%
49725887240 1
< 0.1%
28521529880 1
< 0.1%
28026090180 1
< 0.1%
25851259280 1
< 0.1%
24571443960 1
< 0.1%
15337514890 1
< 0.1%
13951449960 1
< 0.1%
12854691250 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2265
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean234.39483
Minimum0
Maximum123583
Zeros28
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-18T12:33:11.449214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q136
median55
Q3110.25
95-th percentile571.041
Maximum123583
Range123583
Interquartile range (IQR)74.25

Descriptive statistics

Standard deviation2076.0225
Coefficient of variation (CV)8.8569465
Kurtosis1789.7946
Mean234.39483
Median Absolute Deviation (MAD)27
Skewness37.676158
Sum2343948.3
Variance4309869.4
MonotonicityNot monotonic
2024-03-18T12:33:11.572314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 391
 
3.9%
36.0 176
 
1.8%
45.0 147
 
1.5%
27.0 130
 
1.3%
58.0 126
 
1.3%
40.0 115
 
1.1%
35.0 111
 
1.1%
42.0 108
 
1.1%
33.0 108
 
1.1%
39.0 106
 
1.1%
Other values (2255) 8482
84.8%
ValueCountFrequency (%)
0.0 28
0.3%
0.3 1
 
< 0.1%
0.7 1
 
< 0.1%
1.0 18
0.2%
1.3 1
 
< 0.1%
2.0 11
 
0.1%
2.16 1
 
< 0.1%
2.48 1
 
< 0.1%
2.7 1
 
< 0.1%
3.0 20
0.2%
ValueCountFrequency (%)
123583.0 1
< 0.1%
83521.0 1
< 0.1%
76261.0 1
< 0.1%
56478.277 1
< 0.1%
41966.0 1
< 0.1%
41028.0 1
< 0.1%
35137.0 1
< 0.1%
30050.0 1
< 0.1%
27840.0 1
< 0.1%
20800.0 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
2024-03-18T12:33:11.686357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:11.779489image/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
2024-03-18T12:33:11.861490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:11.931530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-18T12:33:06.419278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:03.684667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.124039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.836126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.347233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.901466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.502900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:03.762549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.199286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.918728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.416261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.983929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.592880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:03.840937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.273349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.998680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.493840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.069268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.680897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:03.910467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.602518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.090568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.608608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.150786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.756889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:03.977938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.682536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.186954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.713257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.225947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.848203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.050120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:04.758233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.271222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:05.801813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:33:06.334948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:33:11.991650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도법정동특수지본번부번동시가표준액연면적기준일자
과세년도1.0000.4370.0000.4250.1390.0710.0000.0081.000
법정동0.4371.0000.0810.8490.4770.1760.0000.0000.437
특수지0.0000.0811.0000.1060.0000.1480.0000.0000.000
본번0.4250.8490.1061.0000.3420.3030.0420.0510.425
부번0.1390.4770.0000.3421.0000.0220.0000.0000.139
동0.0710.1760.1480.3030.0221.0000.0000.0000.071
시가표준액0.0000.0000.0000.0420.0000.0001.0000.9160.000
연면적0.0080.0000.0000.0510.0000.0000.9161.0000.008
기준일자1.0000.4370.0000.4250.1390.0710.0000.0081.000
2024-03-18T12:33:12.100155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도특수지
과세년도1.0000.000
특수지0.0001.000
2024-03-18T12:33:12.185781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적과세년도특수지
법정동1.0000.649-0.2760.1190.1490.0350.3360.062
본번0.6491.000-0.326-0.1580.3480.0560.3260.081
부번-0.276-0.3261.000-0.040-0.095-0.0670.1050.000
동0.119-0.158-0.0401.000-0.244-0.0710.0470.098
시가표준액0.1490.348-0.095-0.2441.0000.7630.0000.000
연면적0.0350.056-0.067-0.0710.7631.0000.0080.000
과세년도0.3360.3260.1050.0470.0000.0081.0000.000
특수지0.0620.0810.0000.0980.0000.0000.0001.000

Missing values

2024-03-18T12:33:06.976943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:33:07.169289image/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
23632인천광역시중구2811020211270143316[ 서해대로449번길 10 ] 0001동 0006호662220023.02021-06-012023-08-10
22491인천광역시중구28110202114701280742418[ 흰바위로59번길 8 ] 0002동 0418호6338124061.02021-06-012023-08-10
42069인천광역시중구281102021147012855052인천광역시 중구 운서동 2855 5동 2호210583980419.02021-06-012023-08-10
74846인천광역시중구281102022148017522390010000인천광역시 중구 운북동 752-23 9001동352800036.02022-06-012023-08-10
25914인천광역시중구2811020211280131781인천광역시 중구 신흥동3가 31-7 8동 1호693000090.02021-06-012023-08-10
69625인천광역시중구2811020221450118731700605[ 영종대로 893 ] 0000동 0605호4601740039.2642022-06-012023-08-10
7473인천광역시중구28110202114501195510108[ 은하수로29번길 36 ] 0000동 0108호8495028071.02021-06-012023-08-10
10732인천광역시중구2811020211490170703201인천광역시 중구 을왕동 707 3동 201호276695330334.02021-06-012023-08-10
39453인천광역시중구2811020211180113390023인천광역시 중구 항동7가 1-33 9002동 3호451200048.02021-06-012023-08-10
64143인천광역시중구281102022145011886701719[ 영종대로 911 ] 0000동 1719호4635529039.55232022-06-012023-08-10
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일
58542인천광역시중구281102022147013093700309[ 흰바위로 103 ] 0000동 0309호5588673059.962022-06-012023-08-10
44649인천광역시중구281102021145011946180211[ 영종진광장로 52 ] 0000동 0211호142464000148.02021-06-012023-08-10
47689인천광역시중구281102021147012850101001[ 영종해안남로321번길 208 ] 0000동 1001호23937572103172.02021-06-012023-08-10
22314인천광역시중구281102021147012913100[ 넙디로 56 ] 0000동 0000호108085720125.02021-06-012023-08-10
30909인천광역시중구2811020211320147011인천광역시 중구 도원동 47 1동 1호80477270446.02021-06-012023-08-10
10367인천광역시중구28110202115101467090050인천광역시 중구 덕교동 467 9005동4680000120.02021-06-012023-08-10
75473인천광역시중구28110202215001345000001[ 남북로128번길 39 ] 0000동 0001호2569968038.882022-06-012023-08-10
17903인천광역시중구281102021145011242290022[ 중산로69번길 11-4 ] 9002동 0002호334800027.02021-06-012023-08-10
1993인천광역시중구2811020211450118861811917[ 자연대로 32 ] 0001동 1917호4057788036.02021-06-012023-08-10
63222인천광역시중구281102022145011953211321[ 은하수로29번길 47 ] 0001동 1321호3384381032.892022-06-012023-08-10

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자데이터기준일# duplicates
0인천광역시중구2811020211180127451인천광역시 중구 항동7가 27-4 5동 1호298800018.02021-06-012023-08-102
1인천광역시중구2811020211180167709[ 연안부두로115번길 6 ] 0000동 0009호1220368069.02021-06-012023-08-102
2인천광역시중구281102021127015450124인천광역시 중구 신흥동2가 54-5 124호631300.02021-06-012023-08-102
3인천광역시중구281102021127015450216인천광역시 중구 신흥동2가 54-5 216호549000.02021-06-012023-08-102
4인천광역시중구281102021127015450224인천광역시 중구 신흥동2가 54-5 224호1281001.02021-06-012023-08-102
5인천광역시중구2811020211280164011인천광역시 중구 신흥동3가 64 1동 1호14471483002929.02021-06-012023-08-102
6인천광역시중구2811020211380161411인천광역시 중구 북성동1가 6-14 1동 1호24480018.02021-06-012023-08-102
7인천광역시중구281102021138019821211[ 월미로233번길 11 ] 0001동 0001호313152840370.02021-06-012023-08-102
8인천광역시중구281102021147012877111인천광역시 중구 운서동 2877-1 1동 1호17998911201991.02021-06-012023-08-102
9인천광역시중구28110202114901818311인천광역시 중구 을왕동 818-3 1동 1호2441196098.02021-06-012023-08-102