Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows10
Duplicate rows (%)0.1%
Total size in memory1.3 MiB
Average record size in memory139.0 B

Variable types

Categorical6
Numeric7
Text1
DateTime1

Dataset

Description부산광역시중구_일반건축물시가표준액_20210809
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15080138

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 10 (0.1%) duplicate rowsDuplicates
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (99.3%)Imbalance
부번 has 2169 (21.7%) zerosZeros
동 has 1677 (16.8%) zerosZeros

Reproduction

Analysis started2023-12-10 16:22:47.951948
Analysis finished2023-12-10 16:22:57.382057
Duration9.43 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

2023-12-11T01:22:57.481026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:57.600753image/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
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

2023-12-11T01:22:57.737477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:57.866474image/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
26110
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26110
2nd row26110
3rd row26110
4th row26110
5th row26110

Common Values

ValueCountFrequency (%)
26110 10000
100.0%

Length

2023-12-11T01:22:58.013813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:58.119210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26110 10000
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 10000
100.0%

Length

2023-12-11T01:22:58.253619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:58.372153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 10000
100.0%

법정동
Real number (ℝ)

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.3565
Minimum101
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:22:58.507593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1108
median123
Q3132
95-th percentile140
Maximum141
Range40
Interquartile range (IQR)24

Descriptive statistics

Standard deviation12.622169
Coefficient of variation (CV)0.104009
Kurtosis-1.2215854
Mean121.3565
Median Absolute Deviation (MAD)11
Skewness-0.040148331
Sum1213565
Variance159.31914
MonotonicityNot monotonic
2023-12-11T01:22:58.679882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
107 1059
 
10.6%
140 744
 
7.4%
124 662
 
6.6%
101 616
 
6.2%
141 474
 
4.7%
130 454
 
4.5%
123 432
 
4.3%
132 359
 
3.6%
122 327
 
3.3%
108 302
 
3.0%
Other values (31) 4571
45.7%
ValueCountFrequency (%)
101 616
6.2%
102 110
 
1.1%
103 89
 
0.9%
104 167
 
1.7%
105 242
 
2.4%
106 91
 
0.9%
107 1059
10.6%
108 302
 
3.0%
109 159
 
1.6%
110 39
 
0.4%
ValueCountFrequency (%)
141 474
4.7%
140 744
7.4%
139 165
 
1.7%
138 74
 
0.7%
137 224
 
2.2%
136 129
 
1.3%
135 60
 
0.6%
134 131
 
1.3%
133 174
 
1.7%
132 359
3.6%

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

2023-12-11T01:22:58.862673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:58.985554image/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
9994 
2
 
6

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 9994
99.9%
2 6
 
0.1%

Length

2023-12-11T01:22:59.104890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:22:59.228546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9994
99.9%
2 6
 
0.1%

본번
Real number (ℝ)

Distinct236
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.2461
Minimum1
Maximum751
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:22:59.393616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q115
median32
Q364
95-th percentile118
Maximum751
Range750
Interquartile range (IQR)49

Descriptive statistics

Standard deviation104.65682
Coefficient of variation (CV)1.8281913
Kurtosis23.652013
Mean57.2461
Median Absolute Deviation (MAD)20
Skewness4.7445648
Sum572461
Variance10953.05
MonotonicityNot monotonic
2023-12-11T01:22:59.580967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23 576
 
5.8%
92 475
 
4.8%
3 464
 
4.6%
2 415
 
4.2%
1 264
 
2.6%
20 223
 
2.2%
37 212
 
2.1%
46 188
 
1.9%
12 187
 
1.9%
10 176
 
1.8%
Other values (226) 6820
68.2%
ValueCountFrequency (%)
1 264
2.6%
2 415
4.2%
3 464
4.6%
4 71
 
0.7%
5 152
 
1.5%
6 79
 
0.8%
7 102
 
1.0%
8 116
 
1.2%
9 90
 
0.9%
10 176
 
1.8%
ValueCountFrequency (%)
751 1
 
< 0.1%
747 1
 
< 0.1%
746 3
 
< 0.1%
743 14
0.1%
742 14
0.1%
741 4
 
< 0.1%
728 6
0.1%
726 1
 
< 0.1%
725 1
 
< 0.1%
712 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct130
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4368
Minimum0
Maximum816
Zeros2169
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:22:59.918652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile26
Maximum816
Range816
Interquartile range (IQR)6

Descriptive statistics

Standard deviation23.711605
Coefficient of variation (CV)3.1884151
Kurtosis264.54352
Mean7.4368
Median Absolute Deviation (MAD)2
Skewness13.243263
Sum74368
Variance562.24023
MonotonicityNot monotonic
2023-12-11T01:23:00.124309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2169
21.7%
1 2169
21.7%
2 1032
10.3%
3 872
8.7%
4 434
 
4.3%
5 415
 
4.2%
6 301
 
3.0%
7 297
 
3.0%
10 277
 
2.8%
9 188
 
1.9%
Other values (120) 1846
18.5%
ValueCountFrequency (%)
0 2169
21.7%
1 2169
21.7%
2 1032
10.3%
3 872
8.7%
4 434
 
4.3%
5 415
 
4.2%
6 301
 
3.0%
7 297
 
3.0%
8 176
 
1.8%
9 188
 
1.9%
ValueCountFrequency (%)
816 1
 
< 0.1%
509 1
 
< 0.1%
449 2
< 0.1%
418 1
 
< 0.1%
391 4
< 0.1%
384 1
 
< 0.1%
345 1
 
< 0.1%
310 4
< 0.1%
306 1
 
< 0.1%
305 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.2238
Minimum0
Maximum6022
Zeros1677
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:00.320781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum6022
Range6022
Interquartile range (IQR)0

Descriptive statistics

Standard deviation349.0821
Coefficient of variation (CV)14.410707
Kurtosis255.68312
Mean24.2238
Median Absolute Deviation (MAD)0
Skewness15.92078
Sum242238
Variance121858.31
MonotonicityNot monotonic
2023-12-11T01:23:00.498875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 7583
75.8%
0 1677
 
16.8%
2 256
 
2.6%
3 122
 
1.2%
6 92
 
0.9%
5 82
 
0.8%
4 73
 
0.7%
102 45
 
0.4%
6012 14
 
0.1%
201 12
 
0.1%
Other values (16) 44
 
0.4%
ValueCountFrequency (%)
0 1677
 
16.8%
1 7583
75.8%
2 256
 
2.6%
3 122
 
1.2%
4 73
 
0.7%
5 82
 
0.8%
6 92
 
0.9%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
6022 8
 
0.1%
6012 14
 
0.1%
5022 8
 
0.1%
5012 8
 
0.1%
2022 3
 
< 0.1%
2012 3
 
< 0.1%
202 1
 
< 0.1%
201 12
 
0.1%
109 3
 
< 0.1%
102 45
0.4%

호
Real number (ℝ)

Distinct1238
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1447.5299
Minimum0
Maximum9001
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:00.719965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile101
Q1103
median302
Q31061.25
95-th percentile8101
Maximum9001
Range9001
Interquartile range (IQR)958.25

Descriptive statistics

Standard deviation2567.3595
Coefficient of variation (CV)1.7736141
Kurtosis2.5851073
Mean1447.5299
Median Absolute Deviation (MAD)201
Skewness2.0758899
Sum14475299
Variance6591334.7
MonotonicityNot monotonic
2023-12-11T01:23:00.926709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 1752
17.5%
201 1111
 
11.1%
301 756
 
7.6%
8101 715
 
7.1%
401 514
 
5.1%
102 337
 
3.4%
501 259
 
2.6%
202 238
 
2.4%
601 135
 
1.4%
303 109
 
1.1%
Other values (1228) 4074
40.7%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 22
0.2%
2 16
0.2%
3 7
 
0.1%
4 2
 
< 0.1%
5 6
 
0.1%
6 4
 
< 0.1%
7 3
 
< 0.1%
8 8
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
9001 1
 
< 0.1%
8801 1
 
< 0.1%
8601 2
 
< 0.1%
8505 1
 
< 0.1%
8502 1
 
< 0.1%
8501 7
0.1%
8413 1
 
< 0.1%
8403 1
 
< 0.1%
8402 1
 
< 0.1%
8401 7
0.1%

물건지
Text

Distinct9436
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T01:23:01.340952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length34
Mean length28.786
Min length20

Characters and Unicode

Total characters287860
Distinct characters82
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9025 ?
Unique (%)90.2%

Sample

1st row부산광역시 중구 해관로 37 0001동 0605호
2nd row부산광역시 중구 대청로126번길 29 0001동 0501호
3rd row부산광역시 중구 광복로37번길 3-3 0001동 0101호
4th row부산광역시 중구 중앙대로 21 0001동 2208호
5th row부산광역시 중구 중앙대로 156 0001동 0301호
ValueCountFrequency (%)
부산광역시 10000
 
16.8%
중구 10000
 
16.8%
0001동 6943
 
11.7%
0101호 1593
 
2.7%
0000동 1150
 
1.9%
0201호 1015
 
1.7%
중앙대로 883
 
1.5%
8101호 715
 
1.2%
0301호 701
 
1.2%
1동 640
 
1.1%
Other values (2405) 25840
43.4%
2023-12-11T01:23:01.926154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49480
17.2%
0 44340
15.4%
1 25161
 
8.7%
중 12640
 
4.4%
광 11515
 
4.0%
구 11336
 
3.9%
동 11180
 
3.9%
시 10312
 
3.6%
부 10173
 
3.5%
산 10107
 
3.5%
Other values (72) 91616
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130971
45.5%
Decimal Number 104502
36.3%
Space Separator 49480
 
17.2%
Dash Punctuation 2907
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 12640
9.7%
광 11515
8.8%
구 11336
8.7%
동 11180
8.5%
시 10312
 
7.9%
부 10173
 
7.8%
산 10107
 
7.7%
역 10000
 
7.6%
호 10000
 
7.6%
로 7538
 
5.8%
Other values (60) 26170
20.0%
Decimal Number
ValueCountFrequency (%)
0 44340
42.4%
1 25161
24.1%
2 8746
 
8.4%
3 6338
 
6.1%
4 4570
 
4.4%
5 3815
 
3.7%
8 3305
 
3.2%
6 2994
 
2.9%
9 2988
 
2.9%
7 2245
 
2.1%
Space Separator
ValueCountFrequency (%)
49480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2907
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156889
54.5%
Hangul 130971
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 12640
9.7%
광 11515
8.8%
구 11336
8.7%
동 11180
8.5%
시 10312
 
7.9%
부 10173
 
7.8%
산 10107
 
7.7%
역 10000
 
7.6%
호 10000
 
7.6%
로 7538
 
5.8%
Other values (60) 26170
20.0%
Common
ValueCountFrequency (%)
49480
31.5%
0 44340
28.3%
1 25161
16.0%
2 8746
 
5.6%
3 6338
 
4.0%
4 4570
 
2.9%
5 3815
 
2.4%
8 3305
 
2.1%
6 2994
 
1.9%
9 2988
 
1.9%
Other values (2) 5152
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156889
54.5%
Hangul 130971
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49480
31.5%
0 44340
28.3%
1 25161
16.0%
2 8746
 
5.6%
3 6338
 
4.0%
4 4570
 
2.9%
5 3815
 
2.4%
8 3305
 
2.1%
6 2994
 
1.9%
9 2988
 
1.9%
Other values (2) 5152
 
3.3%
Hangul
ValueCountFrequency (%)
중 12640
9.7%
광 11515
8.8%
구 11336
8.7%
동 11180
8.5%
시 10312
 
7.9%
부 10173
 
7.8%
산 10107
 
7.7%
역 10000
 
7.6%
호 10000
 
7.6%
로 7538
 
5.8%
Other values (60) 26170
20.0%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct7462
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77538912
Minimum43640
Maximum1.7572787 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:02.113783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43640
5-th percentile1234054.5
Q14743145
median19450445
Q345774840
95-th percentile2.2898749 × 108
Maximum1.7572787 × 1010
Range1.7572743 × 1010
Interquartile range (IQR)41031695

Descriptive statistics

Standard deviation4.5461477 × 108
Coefficient of variation (CV)5.8630533
Kurtosis479.28722
Mean77538912
Median Absolute Deviation (MAD)16599245
Skewness19.617608
Sum7.7538912 × 1011
Variance2.0667459 × 1017
MonotonicityNot monotonic
2023-12-11T01:23:02.276002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29847040 80
 
0.8%
45774840 70
 
0.7%
442700 66
 
0.7%
4239000 47
 
0.5%
3368040 45
 
0.4%
2138400 43
 
0.4%
2851200 41
 
0.4%
38479610 41
 
0.4%
2835000 40
 
0.4%
37907730 31
 
0.3%
Other values (7452) 9496
95.0%
ValueCountFrequency (%)
43640 1
< 0.1%
81040 1
< 0.1%
141960 1
< 0.1%
148480 1
< 0.1%
175120 1
< 0.1%
177600 1
< 0.1%
185380 1
< 0.1%
187910 1
< 0.1%
189090 1
< 0.1%
194400 1
< 0.1%
ValueCountFrequency (%)
17572786700 1
< 0.1%
11463333990 1
< 0.1%
10440970320 1
< 0.1%
10271060470 1
< 0.1%
9422804460 1
< 0.1%
9413347710 1
< 0.1%
8726682880 1
< 0.1%
8224680770 1
< 0.1%
8158027700 1
< 0.1%
8110310120 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5303
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.91029
Minimum0.3209
Maximum13377.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:02.457633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.3209
5-th percentile4.8195
Q120.82
median51.17
Q3119.355
95-th percentile467.76
Maximum13377.68
Range13377.359
Interquartile range (IQR)98.535

Descriptive statistics

Standard deviation440.72012
Coefficient of variation (CV)3.242728
Kurtosis362.25302
Mean135.91029
Median Absolute Deviation (MAD)37.97
Skewness16.00256
Sum1359102.9
Variance194234.22
MonotonicityNot monotonic
2023-12-11T01:23:02.628646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.92 80
 
0.8%
43.72 70
 
0.7%
0.95 66
 
0.7%
9.9 59
 
0.6%
15.7 50
 
0.5%
13.2 48
 
0.5%
6.63 45
 
0.4%
10.5 42
 
0.4%
34.3875 41
 
0.4%
16.5 34
 
0.3%
Other values (5293) 9465
94.7%
ValueCountFrequency (%)
0.3209 3
 
< 0.1%
0.3228 18
0.2%
0.3235 3
 
< 0.1%
0.325 1
 
< 0.1%
0.3267 1
 
< 0.1%
0.33 1
 
< 0.1%
0.3302 1
 
< 0.1%
0.407 2
 
< 0.1%
0.4612 3
 
< 0.1%
0.4617 1
 
< 0.1%
ValueCountFrequency (%)
13377.68 1
< 0.1%
13368.72 1
< 0.1%
12326.59 1
< 0.1%
11986.3 1
< 0.1%
10384.52 1
< 0.1%
7764.04 1
< 0.1%
6455.0 1
< 0.1%
6198.45 1
< 0.1%
6182.3 1
< 0.1%
6028.38 1
< 0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-09 00:00:00
Maximum2021-08-09 00:00:00
2023-12-11T01:23:02.797591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:02.940981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T01:22:55.754984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:50.185010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.621807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.513295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.405995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.240867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.992998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.890399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:50.833262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.744198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.647515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.533838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.348643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.094258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:56.013997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:50.971013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.913240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.753974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.658079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.455549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.199999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:56.132409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.109030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.036055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.892068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.761611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.567153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.302700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:56.284363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.229757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.143042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.037472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.873631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.677234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.405070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:56.409813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.360975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.252900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.170078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.984954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.773668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.499401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:56.554291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:51.507091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:52.376225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:53.294044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.095072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:54.904468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:22:55.626040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:23:03.054727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동호시가표준액연면적
법정동1.0000.0880.6630.1590.1710.3860.1770.150
특수지0.0881.0000.0000.0780.0000.0000.0000.045
본번0.6630.0001.0000.0000.0000.1430.0000.000
부번0.1590.0780.0001.0000.0000.0000.0000.000
동0.1710.0000.0000.0001.0000.0350.0000.000
호0.3860.0000.1430.0000.0351.0000.0000.076
시가표준액0.1770.0000.0000.0000.0000.0001.0000.819
연면적0.1500.0450.0000.0000.0000.0760.8191.000
2023-12-11T01:23:03.223653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동호시가표준액연면적특수지
법정동1.000-0.135-0.260-0.1290.015-0.236-0.2160.067
본번-0.1351.0000.071-0.129-0.0660.0370.0630.000
부번-0.2600.0711.0000.099-0.2090.0420.1810.058
동-0.129-0.1290.0991.000-0.071-0.049-0.0150.000
호0.015-0.066-0.209-0.0711.000-0.003-0.0900.000
시가표준액-0.2360.0370.042-0.049-0.0031.0000.8670.000
연면적-0.2160.0630.181-0.015-0.0900.8671.0000.045
특수지0.0670.0000.0580.0000.0000.0000.0451.000

Missing values

2023-12-11T01:22:56.717450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:22:57.248272image/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
21058부산광역시중구261102020105015071605부산광역시 중구 해관로 37 0001동 0605호3586158035.792021-08-09
1966부산광역시중구2611020201120112201501부산광역시 중구 대청로126번길 29 0001동 0501호622987037.262021-08-09
5827부산광역시중구261102020132011211101부산광역시 중구 광복로37번길 3-3 0001동 0101호1340325052.52021-08-09
3974부산광역시중구2611020201110111012208부산광역시 중구 중앙대로 21 0001동 2208호20256009.62021-08-09
4446부산광역시중구261102020107017691301부산광역시 중구 중앙대로 156 0001동 0301호41582880206.882021-08-09
15385부산광역시중구2611020201150144151101부산광역시 중구 동광길 63-1 0001동 0101호352935033.02021-08-09
19678부산광역시중구261102020124015821301부산광역시 중구 흑교로 6 0001동 0301호162020250182.252021-08-09
15076부산광역시중구2611020201150116210401부산광역시 중구 중구로 130 0000동 0401호1312480050.482021-08-09
21011부산광역시중구261102020103011441302부산광역시 중구 중앙대로 147 0001동 0302호1246506060.512021-08-09
14971부산광역시중구2611020201200112551301부산광역시 중구 대청로 57-16 0001동 0301호4049280053.282021-08-09
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
8656부산광역시중구2611020201320149121403부산광역시 중구 창선동2가 49-12 1동 403호433788019.542021-08-09
18766부산광역시중구261102020127011751101부산광역시 중구 광복로49번길 19-1 0001동 0101호99989970110.22021-08-09
20009부산광역시중구2611020201260125171101부산광역시 중구 부평동4가 25-17 1동 101호2037390060.262021-08-09
23383부산광역시중구2611020201010160341101부산광역시 중구 동영로 113-1 0001동 0101호2162517071.52021-08-09
1210부산광역시중구26110202012401201223부산광역시 중구 대청로 60 0001동 0223호1815043019.032021-08-09
14985부산광역시중구26110202012001127118101부산광역시 중구 대청로 61-3 0001동 8101호37535730125.792021-08-09
21625부산광역시중구2611020201070137351301부산광역시 중구 대청로135번길 16 0001동 0301호21751080113.882021-08-09
4665부산광역시중구26110202011101511301부산광역시 중구 해관로 9-1 0001동 0301호58936560265.482021-08-09
4334부산광역시중구261102020108012301806부산광역시 중구 대교로 133 0001동 0806호6233038064.062021-08-09
9381부산광역시중구2611020201400192001073부산광역시 중구 남포동5가 92 1073호749831010.152021-08-09

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
0부산광역시중구261102020107015281101부산광역시 중구 해관로 79-1 0001동 0101호180375360170.812021-08-094
6부산광역시중구26110202012401472601부산광역시 중구 보수대로24번길 4-1 0000동 0001호981618030.582021-08-093
9부산광역시중구261102020141019881101부산광역시 중구 비프광장로 12-1 0001동 0101호6398910072.552021-08-093
1부산광역시중구2611020201070181201201부산광역시 중구 중앙대로116번길 5 0001동 0201호237075600254.922021-08-092
2부산광역시중구261102020111011101304부산광역시 중구 중앙대로 21 0001동 0304호24792509.42021-08-092
3부산광역시중구2611020201110111011002부산광역시 중구 중앙대로 21 0001동 1002호24792509.42021-08-092
4부산광역시중구2611020201110111011025부산광역시 중구 중앙대로 21 0001동 1025호21363708.12021-08-092
5부산광역시중구2611020201110111018203부산광역시 중구 중앙대로 21 0001동 8203호212688012.62021-08-092
7부산광역시중구261102020127013520101부산광역시 중구 광복중앙로33번길 11 0000동 0101호1485608015.942021-08-092
8부산광역시중구2611020201320147111011부산광역시 중구 광복로 38 0001동 1011호18720005.852021-08-092