Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows7
Duplicate rows (%)0.1%
Total size in memory1.3 MiB
Average record size in memory140.0 B

Variable types

Categorical7
Numeric7
Text1

Dataset

Description부산광역시중구_일반건축물시가표준액_20170601
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 7 (0.1%) duplicate rowsDuplicates
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (99.2%)Imbalance
시가표준액 is highly skewed (γ1 = 21.58714275)Skewed
부번 has 1984 (19.8%) zerosZeros
동 has 1780 (17.8%) zerosZeros

Reproduction

Analysis started2023-12-10 16:23:44.767550
Analysis finished2023-12-10 16:23:54.193555
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

2023-12-11T01:23:54.256719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:54.345998image/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

2023-12-11T01:23:54.438723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:54.536715image/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

2023-12-11T01:23:54.651081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:54.773838image/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
2017
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 10000
100.0%

Length

2023-12-11T01:23:54.899997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:54.994483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 10000
100.0%

법정동
Real number (ℝ)

Distinct41
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.1532
Minimum101
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:55.117582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1109
median124
Q3132
95-th percentile141
Maximum141
Range40
Interquartile range (IQR)23

Descriptive statistics

Standard deviation12.43417
Coefficient of variation (CV)0.1017916
Kurtosis-1.1456623
Mean122.1532
Median Absolute Deviation (MAD)10
Skewness-0.13615205
Sum1221532
Variance154.60859
MonotonicityNot monotonic
2023-12-11T01:23:55.349385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
107 1177
 
11.8%
140 748
 
7.5%
124 701
 
7.0%
101 587
 
5.9%
141 511
 
5.1%
130 480
 
4.8%
123 454
 
4.5%
132 358
 
3.6%
122 319
 
3.2%
126 316
 
3.2%
Other values (31) 4349
43.5%
ValueCountFrequency (%)
101 587
5.9%
102 102
 
1.0%
103 105
 
1.1%
104 64
 
0.6%
105 157
 
1.6%
106 110
 
1.1%
107 1177
11.8%
108 126
 
1.3%
109 79
 
0.8%
110 32
 
0.3%
ValueCountFrequency (%)
141 511
5.1%
140 748
7.5%
139 198
 
2.0%
138 82
 
0.8%
137 220
 
2.2%
136 132
 
1.3%
135 70
 
0.7%
134 129
 
1.3%
133 183
 
1.8%
132 358
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

2023-12-11T01:23:55.548746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:55.634042image/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
9993 
2
 
7

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 9993
99.9%
2 7
 
0.1%

Length

2023-12-11T01:23:55.728206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:55.813788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9993
99.9%
2 7
 
0.1%

본번
Real number (ℝ)

Distinct233
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.691
Minimum1
Maximum747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:55.903003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q115
median33
Q363
95-th percentile116
Maximum747
Range746
Interquartile range (IQR)48

Descriptive statistics

Standard deviation96.552751
Coefficient of variation (CV)1.765423
Kurtosis27.226555
Mean54.691
Median Absolute Deviation (MAD)21
Skewness5.0158177
Sum546910
Variance9322.4338
MonotonicityNot monotonic
2023-12-11T01:23:56.044467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92 454
 
4.5%
23 438
 
4.4%
2 423
 
4.2%
3 399
 
4.0%
1 270
 
2.7%
37 256
 
2.6%
20 253
 
2.5%
12 218
 
2.2%
46 208
 
2.1%
52 176
 
1.8%
Other values (223) 6905
69.0%
ValueCountFrequency (%)
1 270
2.7%
2 423
4.2%
3 399
4.0%
4 65
 
0.7%
5 171
1.7%
6 79
 
0.8%
7 104
 
1.0%
8 130
 
1.3%
9 82
 
0.8%
10 139
 
1.4%
ValueCountFrequency (%)
747 1
 
< 0.1%
746 3
 
< 0.1%
743 14
0.1%
742 10
0.1%
741 2
 
< 0.1%
728 3
 
< 0.1%
727 1
 
< 0.1%
712 2
 
< 0.1%
702 5
 
0.1%
691 2
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct133
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8182
Minimum0
Maximum816
Zeros1984
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:56.179662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile28
Maximum816
Range816
Interquartile range (IQR)6

Descriptive statistics

Standard deviation25.322146
Coefficient of variation (CV)3.2388716
Kurtosis234.31228
Mean7.8182
Median Absolute Deviation (MAD)2
Skewness12.722177
Sum78182
Variance641.21107
MonotonicityNot monotonic
2023-12-11T01:23:56.318418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2251
22.5%
0 1984
19.8%
3 992
9.9%
2 917
9.2%
4 449
 
4.5%
5 446
 
4.5%
7 300
 
3.0%
6 292
 
2.9%
10 266
 
2.7%
9 207
 
2.1%
Other values (123) 1896
19.0%
ValueCountFrequency (%)
0 1984
19.8%
1 2251
22.5%
2 917
9.2%
3 992
9.9%
4 449
 
4.5%
5 446
 
4.5%
6 292
 
2.9%
7 300
 
3.0%
8 182
 
1.8%
9 207
 
2.1%
ValueCountFrequency (%)
816 1
 
< 0.1%
509 1
 
< 0.1%
508 2
 
< 0.1%
449 2
 
< 0.1%
391 4
< 0.1%
384 1
 
< 0.1%
375 1
 
< 0.1%
314 1
 
< 0.1%
310 5
0.1%
306 1
 
< 0.1%

동
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.4061
Minimum0
Maximum6022
Zeros1780
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:56.438222image/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 deviation349.76013
Coefficient of variation (CV)14.330849
Kurtosis258.51019
Mean24.4061
Median Absolute Deviation (MAD)0
Skewness15.991057
Sum244061
Variance122332.15
MonotonicityNot monotonic
2023-12-11T01:23:56.549723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 7407
74.1%
0 1780
 
17.8%
2 284
 
2.8%
3 138
 
1.4%
6 99
 
1.0%
4 86
 
0.9%
5 79
 
0.8%
102 49
 
0.5%
6012 17
 
0.2%
201 14
 
0.1%
Other values (17) 47
 
0.5%
ValueCountFrequency (%)
0 1780
 
17.8%
1 7407
74.1%
2 284
 
2.8%
3 138
 
1.4%
4 86
 
0.9%
5 79
 
0.8%
6 99
 
1.0%
7 1
 
< 0.1%
8 3
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
6022 7
 
0.1%
6012 17
 
0.2%
5022 6
 
0.1%
5012 7
 
0.1%
2022 3
 
< 0.1%
2012 5
 
0.1%
202 1
 
< 0.1%
201 14
 
0.1%
109 4
 
< 0.1%
102 49
0.5%

호
Real number (ℝ)

Distinct1235
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1414.8136
Minimum0
Maximum9001
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:56.693078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile101
Q1102
median301
Q31001
95-th percentile8101
Maximum9001
Range9001
Interquartile range (IQR)899

Descriptive statistics

Standard deviation2580.5083
Coefficient of variation (CV)1.823921
Kurtosis2.5945548
Mean1414.8136
Median Absolute Deviation (MAD)200
Skewness2.0850516
Sum14148136
Variance6659022.9
MonotonicityNot monotonic
2023-12-11T01:23:56.817343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 1870
18.7%
201 1240
 
12.4%
301 810
 
8.1%
8101 740
 
7.4%
401 516
 
5.2%
102 386
 
3.9%
501 285
 
2.9%
202 264
 
2.6%
601 117
 
1.2%
303 99
 
1.0%
Other values (1225) 3673
36.7%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 19
0.2%
2 16
0.2%
3 6
 
0.1%
4 7
 
0.1%
5 9
0.1%
6 1
 
< 0.1%
7 5
 
0.1%
8 7
 
0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
9001 1
 
< 0.1%
8803 1
 
< 0.1%
8601 2
 
< 0.1%
8501 1
 
< 0.1%
8403 1
 
< 0.1%
8402 2
 
< 0.1%
8401 6
0.1%
8323 1
 
< 0.1%
8320 1
 
< 0.1%
8317 1
 
< 0.1%

물건지
Text

Distinct9414
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T01:23:57.069651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length24.5244
Min length20

Characters and Unicode

Total characters245244
Distinct characters86
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

Unique8992 ?
Unique (%)89.9%

Sample

1st row[ 흑교로46번길 3 ] 0001동 0201호
2nd row[ 보수대로124번길 53-1 ] 0001동 0101호
3rd row부산광역시 중구 남포동6가 1 1동 8102호
4th row[ 구덕로 46-1 ] 0000동 0101호
5th row[ 중앙대로 80 ] 0000동 1011호
ValueCountFrequency (%)
17234
29.0%
0001동 6803
 
11.4%
0101호 1674
 
2.8%
부산광역시 1383
 
2.3%
중구 1383
 
2.3%
0000동 1258
 
2.1%
0201호 1126
 
1.9%
중앙대로 856
 
1.4%
0301호 761
 
1.3%
8101호 740
 
1.2%
Other values (2415) 26267
44.2%
2023-12-11T01:23:57.510006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49485
20.2%
0 44779
18.3%
1 25221
 
10.3%
동 11178
 
4.6%
호 9999
 
4.1%
2 8932
 
3.6%
[ 8617
 
3.5%
] 8617
 
3.5%
로 7461
 
3.0%
3 6146
 
2.5%
Other values (76) 64809
26.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104684
42.7%
Other Letter 70900
28.9%
Space Separator 49485
20.2%
Open Punctuation 8617
 
3.5%
Close Punctuation 8617
 
3.5%
Dash Punctuation 2941
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 11178
15.8%
호 9999
14.1%
로 7461
 
10.5%
길 4231
 
6.0%
중 3965
 
5.6%
대 3248
 
4.6%
번 3075
 
4.3%
광 3014
 
4.3%
구 2768
 
3.9%
시 1739
 
2.5%
Other values (62) 20222
28.5%
Decimal Number
ValueCountFrequency (%)
0 44779
42.8%
1 25221
24.1%
2 8932
 
8.5%
3 6146
 
5.9%
4 4383
 
4.2%
5 3855
 
3.7%
8 3322
 
3.2%
9 2961
 
2.8%
6 2856
 
2.7%
7 2229
 
2.1%
Space Separator
ValueCountFrequency (%)
49485
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 8617
100.0%
Close Punctuation
ValueCountFrequency (%)
] 8617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2941
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 174344
71.1%
Hangul 70900
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 11178
15.8%
호 9999
14.1%
로 7461
 
10.5%
길 4231
 
6.0%
중 3965
 
5.6%
대 3248
 
4.6%
번 3075
 
4.3%
광 3014
 
4.3%
구 2768
 
3.9%
시 1739
 
2.5%
Other values (62) 20222
28.5%
Common
ValueCountFrequency (%)
49485
28.4%
0 44779
25.7%
1 25221
14.5%
2 8932
 
5.1%
[ 8617
 
4.9%
] 8617
 
4.9%
3 6146
 
3.5%
4 4383
 
2.5%
5 3855
 
2.2%
8 3322
 
1.9%
Other values (4) 10987
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 174344
71.1%
Hangul 70900
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49485
28.4%
0 44779
25.7%
1 25221
14.5%
2 8932
 
5.1%
[ 8617
 
4.9%
] 8617
 
4.9%
3 6146
 
3.5%
4 4383
 
2.5%
5 3855
 
2.2%
8 3322
 
1.9%
Other values (4) 10987
 
6.3%
Hangul
ValueCountFrequency (%)
동 11178
15.8%
호 9999
14.1%
로 7461
 
10.5%
길 4231
 
6.0%
중 3965
 
5.6%
대 3248
 
4.6%
번 3075
 
4.3%
광 3014
 
4.3%
구 2768
 
3.9%
시 1739
 
2.5%
Other values (62) 20222
28.5%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct7657
Distinct (%)76.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68821450
Minimum46000
Maximum1.6298217 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:57.685088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46000
5-th percentile1077989
Q14306575
median17110980
Q342559218
95-th percentile2.096745 × 108
Maximum1.6298217 × 1010
Range1.6298171 × 1010
Interquartile range (IQR)38252642

Descriptive statistics

Standard deviation3.7683582 × 108
Coefficient of variation (CV)5.4755578
Kurtosis614.99053
Mean68821450
Median Absolute Deviation (MAD)14313920
Skewness21.587143
Sum6.882145 × 1011
Variance1.4200524 × 1017
MonotonicityNot monotonic
2023-12-11T01:23:57.898371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443650 87
 
0.9%
28337920 81
 
0.8%
4276680 56
 
0.6%
2247300 54
 
0.5%
2860200 43
 
0.4%
3328260 42
 
0.4%
2996400 41
 
0.4%
35280910 35
 
0.4%
3745500 30
 
0.3%
1051200 27
 
0.3%
Other values (7647) 9504
95.0%
ValueCountFrequency (%)
46000 1
< 0.1%
60290 1
< 0.1%
120640 1
< 0.1%
127650 1
< 0.1%
142420 1
< 0.1%
151000 1
< 0.1%
173420 1
< 0.1%
174000 1
< 0.1%
175290 1
< 0.1%
207400 1
< 0.1%
ValueCountFrequency (%)
16298217290 1
< 0.1%
10187409230 1
< 0.1%
8700186880 1
< 0.1%
8700013690 1
< 0.1%
8458680740 1
< 0.1%
7628137560 1
< 0.1%
7415347140 1
< 0.1%
7402138370 1
< 0.1%
7385994300 1
< 0.1%
7379502300 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5397
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.44226
Minimum0.24
Maximum13700.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:23:58.075389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.24
5-th percentile4.5985
Q119.8
median55.24
Q3126.2
95-th percentile481.441
Maximum13700.12
Range13699.88
Interquartile range (IQR)106.4

Descriptive statistics

Standard deviation379.40318
Coefficient of variation (CV)2.8012171
Kurtosis355.06955
Mean135.44226
Median Absolute Deviation (MAD)41.65
Skewness14.782727
Sum1354422.6
Variance143946.77
MonotonicityNot monotonic
2023-12-11T01:23:58.240175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.95 87
 
0.9%
41.92 81
 
0.8%
9.9 63
 
0.6%
15.7 59
 
0.6%
13.2 57
 
0.6%
10.5 45
 
0.4%
16.5 42
 
0.4%
6.63 42
 
0.4%
45.29 36
 
0.4%
1.56 35
 
0.4%
Other values (5387) 9453
94.5%
ValueCountFrequency (%)
0.24 1
 
< 0.1%
0.325 1
 
< 0.1%
0.407 1
 
< 0.1%
0.4491 2
 
< 0.1%
0.4612 4
< 0.1%
0.4617 3
< 0.1%
0.4824 1
 
< 0.1%
0.4848 7
0.1%
0.5 1
 
< 0.1%
0.53 1
 
< 0.1%
ValueCountFrequency (%)
13700.12 1
< 0.1%
12326.59 1
< 0.1%
6867.67 1
< 0.1%
6198.45 1
< 0.1%
6038.55 1
< 0.1%
6028.4 1
< 0.1%
6028.28 1
< 0.1%
5616.11 1
< 0.1%
5608.34 1
< 0.1%
5598.35 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20170601
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20170601
2nd row20170601
3rd row20170601
4th row20170601
5th row20170601

Common Values

ValueCountFrequency (%)
20170601 10000
100.0%

Length

2023-12-11T01:23:58.422769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:23:58.549012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20170601 10000
100.0%

Interactions

2023-12-11T01:23:52.798434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:46.790127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.718698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.644336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.658023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.641858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.701566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.924749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:46.912426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.914795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.753489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.791324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.806096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.878973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:53.020802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.017761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.054511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.888790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.910545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.942589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.007020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:53.149211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.147612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.189846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.043463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.069833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.108942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.168902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:53.261113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.276523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.306162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.192536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.220257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.251906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.315046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:53.378603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.407947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.398474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.343958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.347342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.379712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.456996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:53.511752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:47.541531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:48.541985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:49.514093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:50.495379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:51.554799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:23:52.650581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:23:58.651295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동특수지본번부번동호시가표준액연면적
법정동1.0000.0690.6760.1610.1670.3890.1820.152
특수지0.0691.0000.0000.1190.0000.0000.0000.060
본번0.6760.0001.0000.0650.0000.1570.0000.000
부번0.1610.1190.0651.0000.0000.0000.0000.000
동0.1670.0000.0000.0001.0000.0300.0000.000
호0.3890.0000.1570.0000.0301.0000.0000.035
시가표준액0.1820.0000.0000.0000.0000.0001.0000.958
연면적0.1520.0600.0000.0000.0000.0350.9581.000
2023-12-11T01:23:58.805327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동본번부번동호시가표준액연면적특수지
법정동1.000-0.145-0.319-0.1330.073-0.181-0.2170.049
본번-0.1451.0000.066-0.105-0.0630.0450.0520.000
부번-0.3190.0661.0000.097-0.2000.0730.1690.090
동-0.133-0.1050.0971.000-0.078-0.070-0.0110.000
호0.073-0.063-0.200-0.0781.000-0.022-0.0770.000
시가표준액-0.1810.0450.073-0.070-0.0221.0000.8930.000
연면적-0.2170.0520.169-0.011-0.0770.8931.0000.045
특수지0.0490.0000.0900.0000.0000.0000.0451.000

Missing values

2023-12-11T01:23:53.923486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:23:54.106889image/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
20649부산광역시중구2611020171200195141201[ 흑교로46번길 3 ] 0001동 0201호310245047.7320170601
2401부산광역시중구261102017121018151101[ 보수대로124번길 53-1 ] 0001동 0101호94849210192.4720170601
3166부산광역시중구261102017141011018102부산광역시 중구 남포동6가 1 1동 8102호3648240081.020170601
17905부산광역시중구261102017139015130101[ 구덕로 46-1 ] 0000동 0101호28802880109.620170601
12648부산광역시중구2611020171070123101011[ 중앙대로 80 ] 0000동 1011호4436500.9520170601
17934부산광역시중구26110201714001920064부산광역시 중구 남포동5가 92 64호16348804.1620170601
20509부산광역시중구26110201711201401201[ 광복로97번길 18 ] 0001동 0201호179048520788.7620170601
3519부산광역시중구261102017141013012119[ 자갈치로 33 ] 0001동 2119호22473009.920170601
21715부산광역시중구261102017108016901502[ 중앙대로 62 ] 0001동 0502호156600030.020170601
4965부산광역시중구261102017132011521302[ 광복로35번길 6-1 ] 0001동 0302호986580048.620170601
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
10928부산광역시중구261102017125014051601[ 흑교로 19 ] 0001동 0601호410576230477.9720170601
2199부산광역시중구261102017121015721201[ 흑교로81번길 5 ] 0001동 0201호33260760111.2420170601
16663부산광역시중구2611020171400192001180부산광역시 중구 남포동5가 92 1180호900144013.1620170601
7829부산광역시중구261102017129014131201[ 광복로35번길 37 ] 0001동 0201호308430044.720170601
3496부산광역시중구261102017141013012095[ 자갈치로 33 ] 0001동 2095호22473009.920170601
9445부산광역시중구261102017126013620101[ 흑교로25번길 28 ] 0000동 0101호3105949073.1520170601
11300부산광역시중구261102017129011671204[ 광복로35번길 14 ] 0001동 0204호2789980070.120170601
22412부산광역시중구261102017116013521102[ 대청로 113 ] 0001동 0102호44761240197.3620170601
12495부산광역시중구2611020171070185131301[ 충장대로9번길 14 ] 0001동 0301호75632840194.9320170601
4947부산광역시중구261102017132011251101[ 광복로35번길 4-1 ] 0001동 0101호1610683066.1220170601

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
0부산광역시중구261102017111011101708[ 중앙대로 21 ] 0001동 0708호21319209.4201706013
1부산광역시중구2611020171110111012224[ 중앙대로 21 ] 0001동 2224호16443008.7201706012
2부산광역시중구2611020171110111012301[ 중앙대로 21 ] 0001동 2301호18144009.6201706012
3부산광역시중구2611020171110111012420[ 중앙대로 21 ] 0001동 2420호190890010.1201706012
4부산광역시중구2611020171110111012420[ 중앙대로 21 ] 0001동 2420호209790011.1201706012
5부산광역시중구2611020171300121361070[ 중구로 28 ] 0006동 1070호6188603.19201706012
6부산광역시중구26110201713001441135[ 국제시장2길 33 ] 0001동 0035호5745603.04201706012