Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows11
Duplicate rows (%)0.1%
Total size in memory1.3 MiB
Average record size in memory138.0 B

Variable types

Categorical7
Numeric5
Text2
DateTime1

Dataset

Description부산광역시 연제구의 2022년 일반 건축물 시가표준액에 대한 데이터로 물건지, 시가표준액, 연면적 등의 데이터를 제공합니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15081712/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
법정리 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 11 (0.1%) duplicate rowsDuplicates
본번 is highly overall correlated with 법정동High correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
법정동 is highly overall correlated with 본번High correlation
특수지 is highly imbalanced (98.7%)Imbalance
시가표준액 is highly skewed (γ1 = 23.55833169)Skewed
연면적 is highly skewed (γ1 = 21.12072473)Skewed
부번 has 601 (6.0%) zerosZeros
동 has 112 (1.1%) zerosZeros

Reproduction

Analysis started2024-03-14 17:26:18.730936
Analysis finished2024-03-14 17:26:27.096548
Duration8.37 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
부산광역시
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 10000
100.0%

Length

2024-03-15T02:26:27.288297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:27.579052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 10000
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연제구 10000
100.0%

Length

2024-03-15T02:26:27.807683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:27.976257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
연제구 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
26470
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26470
2nd row26470
3rd row26470
4th row26470
5th row26470

Common Values

ValueCountFrequency (%)
26470 10000
100.0%

Length

2024-03-15T02:26:28.307132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:28.605150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26470 10000
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2024-03-15T02:26:28.914781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:29.244298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

법정동
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
101
6985 
102
3015 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row102
2nd row102
3rd row101
4th row101
5th row101

Common Values

ValueCountFrequency (%)
101 6985
69.8%
102 3015
30.1%

Length

2024-03-15T02:26:29.565973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:29.902479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
101 6985
69.8%
102 3015
30.1%

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

2024-03-15T02:26:30.078911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:30.241597image/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
9988 
2
 
12

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 9988
99.9%
2 12
 
0.1%

Length

2024-03-15T02:26:30.405275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:26:30.662560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9988
99.9%
2 12
 
0.1%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct393
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean626.5403
Minimum1
Maximum2374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:26:30.959460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22
Q1243
median453
Q31015
95-th percentile1492
Maximum2374
Range2373
Interquartile range (IQR)772

Descriptive statistics

Standard deviation512.74914
Coefficient of variation (CV)0.81838173
Kurtosis-0.82765809
Mean626.5403
Median Absolute Deviation (MAD)336
Skewness0.6557299
Sum6265403
Variance262911.68
MonotonicityNot monotonic
2024-03-15T02:26:31.215597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302 217
 
2.2%
364 190
 
1.9%
1486 183
 
1.8%
676 172
 
1.7%
243 149
 
1.5%
1487 146
 
1.5%
1489 142
 
1.4%
1490 134
 
1.3%
453 132
 
1.3%
307 121
 
1.2%
Other values (383) 8414
84.1%
ValueCountFrequency (%)
1 109
1.1%
2 73
0.7%
3 38
 
0.4%
9 2
 
< 0.1%
10 73
0.7%
11 10
 
0.1%
14 2
 
< 0.1%
15 65
0.7%
17 62
0.6%
18 55
0.5%
ValueCountFrequency (%)
2374 22
 
0.2%
1518 51
0.5%
1515 4
 
< 0.1%
1501 26
 
0.3%
1500 21
 
0.2%
1498 21
 
0.2%
1497 88
0.9%
1496 93
0.9%
1495 43
0.4%
1494 36
 
0.4%

부번
Real number (ℝ)

ZEROS 

Distinct149
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.6718
Minimum0
Maximum484
Zeros601
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:26:31.483644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q318
95-th percentile70
Maximum484
Range484
Interquartile range (IQR)16

Descriptive statistics

Standard deviation36.604973
Coefficient of variation (CV)2.0713778
Kurtosis55.598894
Mean17.6718
Median Absolute Deviation (MAD)5
Skewness6.1282698
Sum176718
Variance1339.9241
MonotonicityNot monotonic
2024-03-15T02:26:31.798692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1737
17.4%
3 838
 
8.4%
2 768
 
7.7%
0 601
 
6.0%
6 500
 
5.0%
4 482
 
4.8%
5 448
 
4.5%
8 341
 
3.4%
7 308
 
3.1%
10 263
 
2.6%
Other values (139) 3714
37.1%
ValueCountFrequency (%)
0 601
 
6.0%
1 1737
17.4%
2 768
7.7%
3 838
8.4%
4 482
 
4.8%
5 448
 
4.5%
6 500
 
5.0%
7 308
 
3.1%
8 341
 
3.4%
9 231
 
2.3%
ValueCountFrequency (%)
484 14
0.1%
406 2
 
< 0.1%
386 5
 
0.1%
369 1
 
< 0.1%
321 2
 
< 0.1%
317 2
 
< 0.1%
315 1
 
< 0.1%
313 1
 
< 0.1%
310 1
 
< 0.1%
299 2
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct93
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.4418
Minimum0
Maximum9002
Zeros112
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:26:32.189414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile126
Maximum9002
Range9002
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1268.4675
Coefficient of variation (CV)4.7787027
Kurtosis25.976981
Mean265.4418
Median Absolute Deviation (MAD)0
Skewness5.0924925
Sum2654418
Variance1609009.7
MonotonicityNot monotonic
2024-03-15T02:26:32.544874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7846
78.5%
2 360
 
3.6%
5000 228
 
2.3%
101 217
 
2.2%
3 186
 
1.9%
0 112
 
1.1%
104 86
 
0.9%
4 68
 
0.7%
5001 58
 
0.6%
7 57
 
0.6%
Other values (83) 782
 
7.8%
ValueCountFrequency (%)
0 112
 
1.1%
1 7846
78.5%
2 360
 
3.6%
3 186
 
1.9%
4 68
 
0.7%
5 48
 
0.5%
6 56
 
0.6%
7 57
 
0.6%
8 37
 
0.4%
9 32
 
0.3%
ValueCountFrequency (%)
9002 2
 
< 0.1%
9001 8
 
0.1%
9000 48
0.5%
8015 1
 
< 0.1%
8014 6
 
0.1%
8013 1
 
< 0.1%
8012 7
 
0.1%
8011 6
 
0.1%
8010 1
 
< 0.1%
8009 6
 
0.1%

호
Text

Distinct458
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T02:26:34.241050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0806
Min length1

Characters and Unicode

Total characters30806
Distinct characters16
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

Unique135 ?
Unique (%)1.4%

Sample

1st row103
2nd row8103
3rd row1
4th row301
5th row610
ValueCountFrequency (%)
101 2062
20.6%
201 1093
 
10.9%
102 782
 
7.8%
8101 667
 
6.7%
301 646
 
6.5%
401 401
 
4.0%
501 243
 
2.4%
103 220
 
2.2%
202 208
 
2.1%
601 150
 
1.5%
Other values (448) 3528
35.3%
2024-03-15T02:26:36.370197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11272
36.6%
0 9352
30.4%
2 3713
 
12.1%
3 1845
 
6.0%
8 1438
 
4.7%
4 1122
 
3.6%
5 779
 
2.5%
6 538
 
1.7%
7 459
 
1.5%
9 265
 
0.9%
Other values (6) 23
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30783
99.9%
Other Letter 12
 
< 0.1%
Dash Punctuation 8
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11272
36.6%
0 9352
30.4%
2 3713
 
12.1%
3 1845
 
6.0%
8 1438
 
4.7%
4 1122
 
3.6%
5 779
 
2.5%
6 538
 
1.7%
7 459
 
1.5%
9 265
 
0.9%
Other Letter
ValueCountFrequency (%)
상 6
50.0%
가 6
50.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
n 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30791
> 99.9%
Hangul 12
 
< 0.1%
Latin 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11272
36.6%
0 9352
30.4%
2 3713
 
12.1%
3 1845
 
6.0%
8 1438
 
4.7%
4 1122
 
3.6%
5 779
 
2.5%
6 538
 
1.7%
7 459
 
1.5%
9 265
 
0.9%
Latin
ValueCountFrequency (%)
J 1
33.3%
a 1
33.3%
n 1
33.3%
Hangul
ValueCountFrequency (%)
상 6
50.0%
가 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30794
> 99.9%
Hangul 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11272
36.6%
0 9352
30.4%
2 3713
 
12.1%
3 1845
 
6.0%
8 1438
 
4.7%
4 1122
 
3.6%
5 779
 
2.5%
6 538
 
1.7%
7 459
 
1.5%
9 265
 
0.9%
Other values (4) 11
 
< 0.1%
Hangul
ValueCountFrequency (%)
상 6
50.0%
가 6
50.0%

물건지
Text

Distinct9413
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T02:26:37.530353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length25.9646
Min length18

Characters and Unicode

Total characters259646
Distinct characters87
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8929 ?
Unique (%)89.3%

Sample

1st row부산광역시 연제구 연산동 302-1 1동 103호
2nd row[ 토곡남로 8 ] 0001동 8103호
3rd row부산광역시 연제구 거제동 1462-32 1동 1호
4th row[ 아시아드대로 79-1 ] 0001동 0301호
5th row[ 법원로 28 ] 0001동 0610호
ValueCountFrequency (%)
14052
23.4%
0001동 6580
 
10.9%
부산광역시 2974
 
4.9%
연제구 2974
 
4.9%
거제동 2132
 
3.5%
0101호 1428
 
2.4%
1동 1266
 
2.1%
연산동 842
 
1.4%
0201호 791
 
1.3%
8101호 667
 
1.1%
Other values (1772) 26426
43.9%
2024-03-15T02:26:39.197467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50132
19.3%
0 39942
15.4%
1 28415
 
10.9%
동 13190
 
5.1%
2 10034
 
3.9%
호 9999
 
3.9%
[ 7026
 
2.7%
] 7026
 
2.7%
로 7021
 
2.7%
제 6438
 
2.5%
Other values (77) 80423
31.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106145
40.9%
Other Letter 86002
33.1%
Space Separator 50132
19.3%
Open Punctuation 7026
 
2.7%
Close Punctuation 7026
 
2.7%
Dash Punctuation 3315
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 13190
15.3%
호 9999
 
11.6%
로 7021
 
8.2%
제 6438
 
7.5%
연 4081
 
4.7%
산 3828
 
4.5%
시 3724
 
4.3%
거 3464
 
4.0%
길 3094
 
3.6%
번 3089
 
3.6%
Other values (63) 28074
32.6%
Decimal Number
ValueCountFrequency (%)
0 39942
37.6%
1 28415
26.8%
2 10034
 
9.5%
3 5877
 
5.5%
8 4590
 
4.3%
4 4585
 
4.3%
5 3862
 
3.6%
6 3262
 
3.1%
7 3181
 
3.0%
9 2397
 
2.3%
Space Separator
ValueCountFrequency (%)
50132
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 7026
100.0%
Close Punctuation
ValueCountFrequency (%)
] 7026
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3315
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 173644
66.9%
Hangul 86002
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 13190
15.3%
호 9999
 
11.6%
로 7021
 
8.2%
제 6438
 
7.5%
연 4081
 
4.7%
산 3828
 
4.5%
시 3724
 
4.3%
거 3464
 
4.0%
길 3094
 
3.6%
번 3089
 
3.6%
Other values (63) 28074
32.6%
Common
ValueCountFrequency (%)
50132
28.9%
0 39942
23.0%
1 28415
16.4%
2 10034
 
5.8%
[ 7026
 
4.0%
] 7026
 
4.0%
3 5877
 
3.4%
8 4590
 
2.6%
4 4585
 
2.6%
5 3862
 
2.2%
Other values (4) 12155
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173644
66.9%
Hangul 86002
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50132
28.9%
0 39942
23.0%
1 28415
16.4%
2 10034
 
5.8%
[ 7026
 
4.0%
] 7026
 
4.0%
3 5877
 
3.4%
8 4590
 
2.6%
4 4585
 
2.6%
5 3862
 
2.2%
Other values (4) 12155
 
7.0%
Hangul
ValueCountFrequency (%)
동 13190
15.3%
호 9999
 
11.6%
로 7021
 
8.2%
제 6438
 
7.5%
연 4081
 
4.7%
산 3828
 
4.5%
시 3724
 
4.3%
거 3464
 
4.0%
길 3094
 
3.6%
번 3089
 
3.6%
Other values (63) 28074
32.6%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7345
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1357294 × 108
Minimum72760
Maximum2.4776628 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:26:39.631365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum72760
5-th percentile1789740
Q19717120
median37241870
Q386350778
95-th percentile3.5840841 × 108
Maximum2.4776628 × 1010
Range2.4776556 × 1010
Interquartile range (IQR)76633658

Descriptive statistics

Standard deviation5.1127805 × 108
Coefficient of variation (CV)4.5017593
Kurtosis813.2948
Mean1.1357294 × 108
Median Absolute Deviation (MAD)31520970
Skewness23.558332
Sum1.1357294 × 1012
Variance2.6140524 × 1017
MonotonicityNot monotonic
2024-03-15T02:26:40.124427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30635290 56
 
0.6%
1789740 47
 
0.5%
32850990 38
 
0.4%
32017660 35
 
0.4%
30267990 33
 
0.3%
51097650 32
 
0.3%
33688770 32
 
0.3%
62550250 31
 
0.3%
28743750 30
 
0.3%
52738380 29
 
0.3%
Other values (7335) 9637
96.4%
ValueCountFrequency (%)
72760 1
 
< 0.1%
75950 1
 
< 0.1%
76630 4
< 0.1%
89600 1
 
< 0.1%
90000 1
 
< 0.1%
112500 1
 
< 0.1%
124200 1
 
< 0.1%
136800 1
 
< 0.1%
140530 1
 
< 0.1%
149040 1
 
< 0.1%
ValueCountFrequency (%)
24776628450 1
< 0.1%
17004628430 1
< 0.1%
13431491000 1
< 0.1%
10897033900 1
< 0.1%
10587147440 1
< 0.1%
9667270180 1
< 0.1%
9238980030 1
< 0.1%
8622654460 1
< 0.1%
8062557360 1
< 0.1%
7978566420 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5667
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195.41108
Minimum0.098
Maximum27377.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T02:26:40.372964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.098
5-th percentile9.45
Q137.16
median82.49
Q3154.895
95-th percentile672.464
Maximum27377.49
Range27377.392
Interquartile range (IQR)117.735

Descriptive statistics

Standard deviation718.75484
Coefficient of variation (CV)3.6781683
Kurtosis615.08213
Mean195.41108
Median Absolute Deviation (MAD)50.79
Skewness21.120725
Sum1954110.8
Variance516608.51
MonotonicityNot monotonic
2024-03-15T02:26:40.811715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 102
 
1.0%
27.0 70
 
0.7%
36.3408 56
 
0.6%
7.9 48
 
0.5%
47.7 45
 
0.4%
46.49 41
 
0.4%
98.3 38
 
0.4%
46.07 34
 
0.3%
51.25 33
 
0.3%
9.0 32
 
0.3%
Other values (5657) 9501
95.0%
ValueCountFrequency (%)
0.098 4
< 0.1%
0.42 1
 
< 0.1%
0.56 1
 
< 0.1%
0.78 1
 
< 0.1%
0.91 2
< 0.1%
0.97 1
 
< 0.1%
1.0 2
< 0.1%
1.02 1
 
< 0.1%
1.03 1
 
< 0.1%
1.05 1
 
< 0.1%
ValueCountFrequency (%)
27377.49 1
< 0.1%
23857.0 1
< 0.1%
23506.1 1
< 0.1%
21730.48 1
< 0.1%
19355.3 1
< 0.1%
14931.3 1
< 0.1%
11899.67 1
< 0.1%
10988.1 1
< 0.1%
10189.74 1
< 0.1%
10004.7 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-06-01 00:00:00
Maximum2022-06-01 00:00:00
2024-03-15T02:26:41.218732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:41.536775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-15T02:26:24.577549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:20.027772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:21.271605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:22.413955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:23.552216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:24.850508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:20.275589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:21.421354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:22.658990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:23.708896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:25.107096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:20.527856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:21.638609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:22.921143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:23.874267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:25.359952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:20.777578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:21.890237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:23.148333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:24.064646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:25.622406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:21.041511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:22.152283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:23.308824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:26:24.313376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:26:41.764524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동시가표준액연면적
법정동1.0000.0270.8770.1180.0940.0000.023
특수지0.0271.0000.0730.0000.0000.0000.000
본번0.8770.0731.0000.2980.1840.3650.268
부번0.1180.0000.2981.0000.0700.0000.000
동0.0940.0000.1840.0701.0000.0000.000
시가표준액0.0000.0000.3650.0000.0001.0000.895
연면적0.0230.0000.2680.0000.0000.8951.000
2024-03-15T02:26:42.274723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지
법정동1.0000.017
특수지0.0171.000
2024-03-15T02:26:42.516793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본번부번동시가표준액연면적법정동특수지
본번1.000-0.304-0.0450.1030.0340.7000.055
부번-0.3041.000-0.214-0.197-0.0670.0900.000
동-0.045-0.2141.000-0.103-0.1830.1150.000
시가표준액0.103-0.197-0.1031.0000.8720.0000.000
연면적0.034-0.067-0.1830.8721.0000.0230.000
법정동0.7000.0900.1150.0000.0231.0000.017
특수지0.0550.0000.0000.0000.0000.0171.000

Missing values

2024-03-15T02:26:26.215319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:26:26.827325image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
4312부산광역시연제구2647020221020130211103부산광역시 연제구 연산동 302-1 1동 103호773430010.152022-06-01
5241부산광역시연제구2647020221020157618103[ 토곡남로 8 ] 0001동 8103호2640627088.912022-06-01
6515부산광역시연제구2647020221010114623211부산광역시 연제구 거제동 1462-32 1동 1호300899073.392022-06-01
9297부산광역시연제구2647020221010190061301[ 아시아드대로 79-1 ] 0001동 0301호4622592099.842022-06-01
2704부산광역시연제구26470202210101149011610[ 법원로 28 ] 0001동 0610호91859150144.362022-06-01
8691부산광역시연제구26470202210101148631503[ 법원남로16번길 27 ] 0001동 0503호3026799046.072022-06-01
6327부산광역시연제구264702022101015001518101[ 거제대로124번길 36 ] 0001동 8101호15950106.732022-06-01
6063부산광역시연제구26470202210101148931301[ 법원남로 12 ] 0001동 0301호540392210489.48572022-06-01
9633부산광역시연제구2647020221010148741201[ 거제시장로11번길 8 ] 0001동 0201호9724260106.862022-06-01
771부산광역시연제구2647020221010111211101[ 중앙대로1249번길 27 ] 0001동 0101호1095088084.272022-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
5918부산광역시연제구26470202210101149111703[ 법원로 20 ] 0001동 0703호115023190131.612022-06-01
9530부산광역시연제구2647020221010190081708[ 월드컵대로 282 ] 0001동 0708호3368877051.252022-06-01
5656부산광역시연제구26470202210101149011909[ 법원로 28 ] 0001동 0909호70892410111.412022-06-01
8476부산광역시연제구26470202210101148621103[ 법원북로 86 ] 0001동 0103호4714400058.932022-06-01
6268부산광역시연제구26470202210101139621105부산광역시 연제구 거제동 1396-2 1동 105호87050360220.942022-06-01
434부산광역시연제구2647020221010135401301[ 교대로54번길 24 ] 0001동 0301호81402480120.242022-06-01
8225부산광역시연제구26470202210101148711809[ 법원로 34 ] 0001동 0809호5369904084.392022-06-01
1356부산광역시연제구264702022101014211011602[ 명륜로2번길 11 ] 0101동 1602호3332441031.40852022-06-01
6218부산광역시연제구26470202210101987198101[ 아시아드대로64번길 20-4 ] 0009동 8101호5939103.972022-06-01
2759부산광역시연제구26470202210201360441103부산광역시 연제구 연산동 360-44 1동 103호96900051.02022-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
3부산광역시연제구264702022101017911023101부산광역시 연제구 거제동 791-10 23동 101호22590009.02022-06-016
8부산광역시연제구26470202210101149661101[ 법원남로15번길 29 ] 0001동 0101호138052380127.592022-06-014
0부산광역시연제구264702022101017011101[ 명륜로2번길 8 ] 0001동 0101호7922252083.482022-06-012
1부산광역시연제구2647020221010141234101부산광역시 연제구 거제동 412-3 4동 101호351000015.02022-06-012
2부산광역시연제구264702022101017911023101부산광역시 연제구 거제동 791-10 23동 101호11069104.412022-06-012
4부산광역시연제구264702022101017911023101부산광역시 연제구 거제동 791-10 23동 101호451800018.02022-06-012
5부산광역시연제구264702022101017911023101부산광역시 연제구 거제동 791-10 23동 101호677700027.02022-06-012
6부산광역시연제구26470202210101146345101부산광역시 연제구 거제동 1463-4 5동 101호565200018.02022-06-012
7부산광역시연제구26470202210101146346101부산광역시 연제구 거제동 1463-4 6동 101호1130400036.02022-06-012
9부산광역시연제구26470202210201243246101부산광역시 연제구 연산동 243-24 6동 101호307800018.02022-06-012