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
Numeric6
Text2

Dataset

Description부산광역시 중구 일반건축물 시가표준액에 대한 데이터로 시도명, 시군구명, 자치단체코드, 과세년도, 법정동, 법정리, 특수지, 본번, 부번, 동, 호, 물건지, 시가표준액, 연면적, 기준일자 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15080138/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
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (98.9%)Imbalance
부번 has 2231 (22.3%) zerosZeros
동 has 1644 (16.4%) zerosZeros

Reproduction

Analysis started2023-12-12 20:04:04.007738
Analysis finished2023-12-12 20:04:10.996124
Duration6.99 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

2023-12-13T05:04:11.053022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:11.133075image/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

2023-12-13T05:04:11.224902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:11.312258image/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

2023-12-13T05:04:11.402840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:11.500081image/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
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

2023-12-13T05:04:11.592501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:11.683452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

법정동
Real number (ℝ)

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.6158
Minimum101
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:11.823323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1108
median123
Q3132
95-th percentile141
Maximum141
Range40
Interquartile range (IQR)24

Descriptive statistics

Standard deviation12.741029
Coefficient of variation (CV)0.10476459
Kurtosis-1.2377423
Mean121.6158
Median Absolute Deviation (MAD)12
Skewness-0.048583657
Sum1216158
Variance162.33382
MonotonicityNot monotonic
2023-12-13T05:04:12.028207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
107 1230
 
12.3%
140 775
 
7.8%
101 624
 
6.2%
124 622
 
6.2%
141 518
 
5.2%
130 453
 
4.5%
123 408
 
4.1%
132 345
 
3.5%
122 334
 
3.3%
120 289
 
2.9%
Other values (31) 4402
44.0%
ValueCountFrequency (%)
101 624
6.2%
102 102
 
1.0%
103 87
 
0.9%
104 94
 
0.9%
105 214
 
2.1%
106 96
 
1.0%
107 1230
12.3%
108 222
 
2.2%
109 166
 
1.7%
110 28
 
0.3%
ValueCountFrequency (%)
141 518
5.2%
140 775
7.8%
139 247
 
2.5%
138 76
 
0.8%
137 208
 
2.1%
136 133
 
1.3%
135 43
 
0.4%
134 136
 
1.4%
133 149
 
1.5%
132 345
3.5%

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

2023-12-13T05:04:12.186674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:12.284607image/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
9990 
2
 
10

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 9990
99.9%
2 10
 
0.1%

Length

2023-12-13T05:04:12.384428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:12.484349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9990
99.9%
2 10
 
0.1%

본번
Real number (ℝ)

Distinct226
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.3192
Minimum1
Maximum747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:12.662143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median33
Q369
95-th percentile123
Maximum747
Range746
Interquartile range (IQR)55

Descriptive statistics

Standard deviation105.72489
Coefficient of variation (CV)1.8128659
Kurtosis22.617353
Mean58.3192
Median Absolute Deviation (MAD)23
Skewness4.646927
Sum583192
Variance11177.752
MonotonicityNot monotonic
2023-12-13T05:04:12.882443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 511
 
5.1%
92 460
 
4.6%
2 407
 
4.1%
23 359
 
3.6%
1 260
 
2.6%
37 212
 
2.1%
20 210
 
2.1%
19 200
 
2.0%
46 196
 
2.0%
12 187
 
1.9%
Other values (216) 6998
70.0%
ValueCountFrequency (%)
1 260
2.6%
2 407
4.1%
3 511
5.1%
4 81
 
0.8%
5 159
 
1.6%
6 81
 
0.8%
7 172
 
1.7%
8 106
 
1.1%
9 99
 
1.0%
10 161
 
1.6%
ValueCountFrequency (%)
747 1
 
< 0.1%
746 1
 
< 0.1%
743 12
0.1%
742 7
0.1%
741 4
 
< 0.1%
728 6
0.1%
727 1
 
< 0.1%
702 4
 
< 0.1%
694 3
 
< 0.1%
688 1
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct125
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4476
Minimum0
Maximum816
Zeros2231
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:13.073763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile27
Maximum816
Range816
Interquartile range (IQR)6

Descriptive statistics

Standard deviation24.693174
Coefficient of variation (CV)3.3155881
Kurtosis275.3119
Mean7.4476
Median Absolute Deviation (MAD)2
Skewness13.532415
Sum74476
Variance609.75283
MonotonicityNot monotonic
2023-12-13T05:04:13.264915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2231
22.3%
1 2217
22.2%
2 974
9.7%
3 859
 
8.6%
5 443
 
4.4%
4 428
 
4.3%
6 314
 
3.1%
7 291
 
2.9%
10 270
 
2.7%
9 196
 
2.0%
Other values (115) 1777
17.8%
ValueCountFrequency (%)
0 2231
22.3%
1 2217
22.2%
2 974
9.7%
3 859
 
8.6%
4 428
 
4.3%
5 443
 
4.4%
6 314
 
3.1%
7 291
 
2.9%
8 174
 
1.7%
9 196
 
2.0%
ValueCountFrequency (%)
816 1
 
< 0.1%
694 1
 
< 0.1%
509 1
 
< 0.1%
449 1
 
< 0.1%
437 1
 
< 0.1%
391 2
 
< 0.1%
384 2
 
< 0.1%
355 1
 
< 0.1%
345 1
 
< 0.1%
310 5
0.1%

동
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.181
Minimum0
Maximum6022
Zeros1644
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:13.415906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum6022
Range6022
Interquartile range (IQR)0

Descriptive statistics

Standard deviation374.05503
Coefficient of variation (CV)13.273306
Kurtosis229.13712
Mean28.181
Median Absolute Deviation (MAD)0
Skewness15.082846
Sum281810
Variance139917.16
MonotonicityNot monotonic
2023-12-13T05:04:13.533760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 7513
75.1%
0 1644
 
16.4%
2 231
 
2.3%
3 142
 
1.4%
103 108
 
1.1%
5 86
 
0.9%
6 86
 
0.9%
4 66
 
0.7%
102 42
 
0.4%
6012 21
 
0.2%
Other values (19) 61
 
0.6%
ValueCountFrequency (%)
0 1644
 
16.4%
1 7513
75.1%
2 231
 
2.3%
3 142
 
1.4%
4 66
 
0.7%
5 86
 
0.9%
6 86
 
0.9%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 5
 
0.1%
ValueCountFrequency (%)
6022 8
 
0.1%
6012 21
 
0.2%
5022 7
 
0.1%
5012 6
 
0.1%
2022 3
 
< 0.1%
2012 4
 
< 0.1%
202 1
 
< 0.1%
201 10
 
0.1%
109 4
 
< 0.1%
103 108
1.1%

호
Text

Distinct1237
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:04:13.997882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.9995
Min length3

Characters and Unicode

Total characters39995
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique556 ?
Unique (%)5.6%

Sample

1st row1001
2nd row0121
3rd row0101
4th row8108
5th row0801
ValueCountFrequency (%)
0101 1679
16.8%
0201 1126
 
11.3%
0301 738
 
7.4%
8101 650
 
6.5%
0401 516
 
5.2%
0102 333
 
3.3%
0501 266
 
2.7%
0202 253
 
2.5%
0601 149
 
1.5%
0302 104
 
1.0%
Other values (1227) 4186
41.9%
2023-12-13T05:04:14.598698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16881
42.2%
1 11066
27.7%
2 3747
 
9.4%
3 2108
 
5.3%
8 1695
 
4.2%
4 1454
 
3.6%
5 1064
 
2.7%
6 850
 
2.1%
7 661
 
1.7%
9 468
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39994
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16881
42.2%
1 11066
27.7%
2 3747
 
9.4%
3 2108
 
5.3%
8 1695
 
4.2%
4 1454
 
3.6%
5 1064
 
2.7%
6 850
 
2.1%
7 661
 
1.7%
9 468
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16881
42.2%
1 11066
27.7%
2 3747
 
9.4%
3 2108
 
5.3%
8 1695
 
4.2%
4 1454
 
3.6%
5 1064
 
2.7%
6 850
 
2.1%
7 661
 
1.7%
9 468
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16881
42.2%
1 11066
27.7%
2 3747
 
9.4%
3 2108
 
5.3%
8 1695
 
4.2%
4 1454
 
3.6%
5 1064
 
2.7%
6 850
 
2.1%
7 661
 
1.7%
9 468
 
1.2%

물건지
Text

Distinct9504
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:04:15.019341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length29.8105
Min length20

Characters and Unicode

Total characters298105
Distinct characters85
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9180 ?
Unique (%)91.8%

Sample

1st row부산광역시 중구 중구로 46, 0002동 1001호
2nd row부산광역시 중구 남포동5가 92 121호
3rd row부산광역시 중구 자갈치로60번길 6, 0001동 0101호
4th row부산광역시 중구 중앙동4가 79-1 1동 8108호
5th row부산광역시 중구 광복중앙로33번길 16, 0001동 0801호
ValueCountFrequency (%)
부산광역시 10000
 
16.8%
중구 10000
 
16.8%
0001동 7005
 
11.8%
0101호 1523
 
2.6%
0000동 1129
 
1.9%
0201호 1043
 
1.8%
중앙대로 751
 
1.3%
0301호 687
 
1.2%
8101호 650
 
1.1%
대청로 557
 
0.9%
Other values (2367) 26147
44.0%
2023-12-13T05:04:15.619638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49492
16.6%
0 44608
15.0%
1 25339
 
8.5%
중 12429
 
4.2%
광 11442
 
3.8%
구 11355
 
3.8%
동 11011
 
3.7%
시 10343
 
3.5%
부 10169
 
3.4%
산 10140
 
3.4%
Other values (75) 101777
34.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 131544
44.1%
Decimal Number 105414
35.4%
Space Separator 49492
 
16.6%
Other Punctuation 8759
 
2.9%
Dash Punctuation 2896
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 12429
9.4%
광 11442
8.7%
구 11355
8.6%
동 11011
8.4%
시 10343
 
7.9%
부 10169
 
7.7%
산 10140
 
7.7%
역 10000
 
7.6%
호 9998
 
7.6%
로 7621
 
5.8%
Other values (62) 27036
20.6%
Decimal Number
ValueCountFrequency (%)
0 44608
42.3%
1 25339
24.0%
2 8891
 
8.4%
3 6227
 
5.9%
4 4612
 
4.4%
5 4099
 
3.9%
8 3213
 
3.0%
9 3112
 
3.0%
6 2944
 
2.8%
7 2369
 
2.2%
Space Separator
ValueCountFrequency (%)
49492
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8759
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2896
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 166561
55.9%
Hangul 131544
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 12429
9.4%
광 11442
8.7%
구 11355
8.6%
동 11011
8.4%
시 10343
 
7.9%
부 10169
 
7.7%
산 10140
 
7.7%
역 10000
 
7.6%
호 9998
 
7.6%
로 7621
 
5.8%
Other values (62) 27036
20.6%
Common
ValueCountFrequency (%)
49492
29.7%
0 44608
26.8%
1 25339
15.2%
2 8891
 
5.3%
, 8759
 
5.3%
3 6227
 
3.7%
4 4612
 
2.8%
5 4099
 
2.5%
8 3213
 
1.9%
9 3112
 
1.9%
Other values (3) 8209
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166561
55.9%
Hangul 131544
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49492
29.7%
0 44608
26.8%
1 25339
15.2%
2 8891
 
5.3%
, 8759
 
5.3%
3 6227
 
3.7%
4 4612
 
2.8%
5 4099
 
2.5%
8 3213
 
1.9%
9 3112
 
1.9%
Other values (3) 8209
 
4.9%
Hangul
ValueCountFrequency (%)
중 12429
9.4%
광 11442
8.7%
구 11355
8.6%
동 11011
8.4%
시 10343
 
7.9%
부 10169
 
7.7%
산 10140
 
7.7%
역 10000
 
7.6%
호 9998
 
7.6%
로 7621
 
5.8%
Other values (62) 27036
20.6%

시가표준액
Real number (ℝ)

HIGH CORRELATION 

Distinct7339
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77251512
Minimum111050
Maximum1.2081383 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:15.798337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111050
5-th percentile1548800
Q15931782.5
median23407440
Q348367538
95-th percentile2.3973208 × 108
Maximum1.2081383 × 1010
Range1.2081272 × 1010
Interquartile range (IQR)42435755

Descriptive statistics

Standard deviation4.1638837 × 108
Coefficient of variation (CV)5.3900352
Kurtosis426.23091
Mean77251512
Median Absolute Deviation (MAD)19064715
Skewness19.186507
Sum7.7251512 × 1011
Variance1.7337927 × 1017
MonotonicityNot monotonic
2023-12-13T05:04:15.979129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30823530 73
 
0.7%
4651120 58
 
0.6%
3128400 50
 
0.5%
40474080 48
 
0.5%
32571330 46
 
0.5%
2346300 46
 
0.5%
52326990 43
 
0.4%
3494010 39
 
0.4%
3110620 36
 
0.4%
53237740 31
 
0.3%
Other values (7329) 9530
95.3%
ValueCountFrequency (%)
111050 1
< 0.1%
134550 1
< 0.1%
197340 1
< 0.1%
199410 1
< 0.1%
204160 1
< 0.1%
211140 1
< 0.1%
222870 1
< 0.1%
249700 1
< 0.1%
262800 1
< 0.1%
266000 1
< 0.1%
ValueCountFrequency (%)
12081382800 1
< 0.1%
11242318470 1
< 0.1%
10085548040 1
< 0.1%
9933597520 1
< 0.1%
9933399780 1
< 0.1%
9923430590 1
< 0.1%
9575752280 1
< 0.1%
9197499360 1
< 0.1%
8598164460 1
< 0.1%
8441233660 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5333
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.67129
Minimum0.325
Maximum13700.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:04:16.170906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.325
5-th percentile6.4
Q124.49
median51.4
Q3117.79
95-th percentile443.088
Maximum13700.12
Range13699.795
Interquartile range (IQR)93.3

Descriptive statistics

Standard deviation382.58759
Coefficient of variation (CV)2.9733719
Kurtosis455.60956
Mean128.67129
Median Absolute Deviation (MAD)36.595
Skewness17.391976
Sum1286712.9
Variance146373.27
MonotonicityNot monotonic
2023-12-13T05:04:16.313621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.87 73
 
0.7%
9.9 60
 
0.6%
15.7 58
 
0.6%
13.2 53
 
0.5%
34.3875 48
 
0.5%
33.27 46
 
0.5%
50.9527 43
 
0.4%
6.63 40
 
0.4%
16.5 38
 
0.4%
10.5 37
 
0.4%
Other values (5323) 9504
95.0%
ValueCountFrequency (%)
0.325 1
< 0.1%
0.4921 2
< 0.1%
0.66 1
< 0.1%
0.7 1
< 0.1%
0.71 1
< 0.1%
0.72 1
< 0.1%
0.8878 1
< 0.1%
0.93 1
< 0.1%
1.0227 2
< 0.1%
1.069 2
< 0.1%
ValueCountFrequency (%)
13700.12 1
< 0.1%
13377.68 1
< 0.1%
10523.0 1
< 0.1%
9294.55 1
< 0.1%
6182.3 1
< 0.1%
6028.4 1
< 0.1%
6028.38 1
< 0.1%
6028.28 1
< 0.1%
6022.23 1
< 0.1%
5958.12 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022-06-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2022-06-01 10000
100.0%

Length

2023-12-13T05:04:16.435097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:16.513372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-01 10000
100.0%

Interactions

2023-12-13T05:04:10.002951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.010877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.800848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.633998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.450134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.126293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:10.107883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.139353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.944898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.785671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.547621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.231959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:10.228294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.263979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.070640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.906770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.635898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.598329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:10.329483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.404741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.199912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.046381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.742869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.706926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:10.420283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.545220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.328167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.175996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.855646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.805340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:10.529446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:06.679481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:07.471953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:08.321588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.006048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:09.905566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:04:16.566845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동시가표준액연면적
법정동1.0000.0840.6830.1580.1840.2210.145
특수지0.0841.0000.0000.1570.0000.0000.000
본번0.6830.0001.0000.0000.0000.0000.009
부번0.1580.1570.0001.0000.0000.0000.000
동0.1840.0000.0000.0001.0000.0000.000
시가표준액0.2210.0000.0000.0000.0001.0000.879
연면적0.1450.0000.0090.0000.0000.8791.000
2023-12-13T05:04:16.660821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동시가표준액연면적특수지
법정동1.000-0.170-0.266-0.203-0.251-0.2510.060
본번-0.1701.0000.057-0.1170.0250.0600.000
부번-0.2660.0571.0000.0760.0250.1960.156
동-0.203-0.1170.0761.000-0.064-0.0400.000
시가표준액-0.2510.0250.025-0.0641.0000.8440.000
연면적-0.2510.0600.196-0.0400.8441.0000.000
특수지0.0600.0000.1560.0000.0000.0001.000

Missing values

2023-12-13T05:04:10.677489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:04:10.897668image/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
202부산광역시중구2611020221300141321001부산광역시 중구 중구로 46, 0002동 1001호138012014.842022-06-01
5829부산광역시중구2611020221400192000121부산광역시 중구 남포동5가 92 121호750814015.592022-06-01
5514부산광역시중구26110202214001114410101부산광역시 중구 자갈치로60번길 6, 0001동 0101호2324380081.52022-06-01
17050부산광역시중구2611020221070179118108부산광역시 중구 중앙동4가 79-1 1동 8108호4100901.872022-06-01
13190부산광역시중구2611020221280121110801부산광역시 중구 광복중앙로33번길 16, 0001동 0801호16608908.762022-06-01
12544부산광역시중구2611020221240136610401부산광역시 중구 광복로12번길 10-1, 0001동 0401호38615940159.572022-06-01
20467부산광역시중구261102022117019611006부산광역시 중구 복병산길3번길 9, 0001동 1006호3893734042.32322022-06-01
11095부산광역시중구2611020221250124510601부산광역시 중구 흑교로25번길 2, 0001동 0601호121529760123.772022-06-01
5067부산광역시중구2611020221400188010202부산광역시 중구 자갈치로37번길 4, 0001동 0202호253704010.232022-06-01
12495부산광역시중구2611020221300120160120044부산광역시 중구 국제시장2길 9, 6012동 0044호15972006.62022-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
14231부산광역시중구2611020221280130210201부산광역시 중구 중구로40번길 11-1, 0001동 0201호70840660292.732022-06-01
8037부산광역시중구26110202212301411010102부산광역시 중구 광복로16번길 18, 0001동 0102호59268360131.812022-06-01
114부산광역시중구2611020221340134010401부산광역시 중구 광복로 72-1, 0001동 0401호29492190108.032022-06-01
19856부산광역시중구261102022109018010201부산광역시 중구 중앙동6가 8 1동 201호68625860148.222022-06-01
13240부산광역시중구2611020221300127150127부산광역시 중구 국제시장2길 15, 0005동 0127호21483009.32022-06-01
17769부산광역시중구2611020221070158110201부산광역시 중구 해관로 82, 0001동 0201호75140340138.382022-06-01
2385부산광역시중구261102022137013510201부산광역시 중구 남포길 43-1, 0001동 0201호1644780047.42022-06-01
1324부산광역시중구2611020221320148110201부산광역시 중구 광복로 40, 0001동 0201호28031640102.682022-06-01
19984부산광역시중구2611020221170142210002부산광역시 중구 복병산길7번길 3, 0001동 0002호69288780182.822022-06-01
9491부산광역시중구2611020221220115100202부산광역시 중구 흑교로75번길 18, 0000동 0202호2879240031.852022-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
0부산광역시중구2611020221070152810101부산광역시 중구 해관로 79-1, 0001동 0101호188915860170.812022-06-013
1부산광역시중구2611020221110111010303부산광역시 중구 중앙대로 21, 0001동 0303호27431209.52022-06-012
2부산광역시중구2611020221110111010708부산광역시 중구 중앙대로 21, 0001동 0708호27142509.42022-06-012
3부산광역시중구2611020221110111012229부산광역시 중구 중앙대로 21, 0001동 2229호22176009.62022-06-012
4부산광역시중구2611020221110111012301부산광역시 중구 중앙대로 21, 0001동 2301호22176009.62022-06-012
5부산광역시중구2611020221210138110101부산광역시 중구 흑교로87번길 3-1, 0001동 0101호504900019.82022-06-012
6부산광역시중구26110202212101861210001부산광역시 중구 흑교로 63-1, 0001동 0001호2056230034.12022-06-012
7부산광역시중구2611020221270135200101부산광역시 중구 광복중앙로33번길 11, 0000동 0101호1549368015.942022-06-012
8부산광역시중구2611020221300121360221113부산광역시 중구 중구로 28, 6022동 1113호7484403.242022-06-012
9부산광역시중구2611020221300150218101부산광역시 중구 중구로 52, 0001동 8101호25558509.8342022-06-012