Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows17
Duplicate rows (%)0.2%
Total size in memory1.3 MiB
Average record size in memory138.0 B

Variable types

Categorical7
Numeric6
Text2

Dataset

Description제공범위 : 일반건축물에 대한 지방세 부과기준인 시가표준액을 제공. 관련 법령 : 지방세법. 소관기관 : 지방자치단체. 제공기관 : 시군구. 표준데이터 셋 제공시스템 : 표준지방세시스템. 자료기준일 : 매년 12월 31일.
URLhttps://www.data.go.kr/data/15080111/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세년도 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 17 (0.2%) duplicate rowsDuplicates
특수지 is highly imbalanced (94.9%)Imbalance
동 is highly imbalanced (80.8%)Imbalance
부번 has 3667 (36.7%) zerosZeros

Reproduction

Analysis started2023-12-12 16:28:38.692419
Analysis finished2023-12-12 16:28:45.973801
Duration7.28 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
충청남도
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 10000
100.0%

Length

2023-12-13T01:28:46.063155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:46.203985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 10000
100.0%

시군구명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홍성군 10000
100.0%

Length

2023-12-13T01:28:46.316481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:46.425732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홍성군 10000
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
44800
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row44800
2nd row44800
3rd row44800
4th row44800
5th row44800

Common Values

ValueCountFrequency (%)
44800 10000
100.0%

Length

2023-12-13T01:28:46.523877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:46.643287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
44800 10000
100.0%

과세년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2021 10000
100.0%

Length

2023-12-13T01:28:46.740199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:46.834704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

법정동
Real number (ℝ)

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.5094
Minimum250
Maximum390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:46.941742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile250
Q1253
median256
Q3350
95-th percentile390
Maximum390
Range140
Interquartile range (IQR)97

Descriptive statistics

Standard deviation53.224229
Coefficient of variation (CV)0.17652594
Kurtosis-1.5952064
Mean301.5094
Median Absolute Deviation (MAD)6
Skewness0.32784411
Sum3015094
Variance2832.8186
MonotonicityNot monotonic
2023-12-13T01:28:47.047004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
250 2398
24.0%
256 1608
16.1%
253 1172
11.7%
330 733
 
7.3%
350 663
 
6.6%
390 593
 
5.9%
380 590
 
5.9%
340 586
 
5.9%
320 579
 
5.8%
370 542
 
5.4%
ValueCountFrequency (%)
250 2398
24.0%
253 1172
11.7%
256 1608
16.1%
320 579
 
5.8%
330 733
 
7.3%
340 586
 
5.9%
350 663
 
6.6%
360 536
 
5.4%
370 542
 
5.4%
380 590
 
5.9%
ValueCountFrequency (%)
390 593
 
5.9%
380 590
 
5.9%
370 542
 
5.4%
360 536
 
5.4%
350 663
6.6%
340 586
 
5.9%
330 733
7.3%
320 579
 
5.8%
256 1608
16.1%
253 1172
11.7%

법정리
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.6899
Minimum21
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:47.166143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q122
median25
Q329
95-th percentile32
Maximum36
Range15
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.7315855
Coefficient of variation (CV)0.14525496
Kurtosis-0.67951128
Mean25.6899
Median Absolute Deviation (MAD)3
Skewness0.53744549
Sum256899
Variance13.92473
MonotonicityNot monotonic
2023-12-13T01:28:47.297589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
25 1650
16.5%
21 1494
14.9%
22 1218
12.2%
24 818
8.2%
30 710
7.1%
26 641
 
6.4%
31 608
 
6.1%
27 591
 
5.9%
23 583
 
5.8%
29 496
 
5.0%
Other values (6) 1191
11.9%
ValueCountFrequency (%)
21 1494
14.9%
22 1218
12.2%
23 583
 
5.8%
24 818
8.2%
25 1650
16.5%
26 641
 
6.4%
27 591
 
5.9%
28 416
 
4.2%
29 496
 
5.0%
30 710
7.1%
ValueCountFrequency (%)
36 46
 
0.5%
35 76
 
0.8%
34 73
 
0.7%
33 277
 
2.8%
32 303
3.0%
31 608
6.1%
30 710
7.1%
29 496
5.0%
28 416
4.2%
27 591
5.9%

특수지
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9903 
2
 
94
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9903
99.0%
2 94
 
0.9%
5 3
 
< 0.1%

Length

2023-12-13T01:28:47.453826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:47.585987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9903
99.0%
2 94
 
0.9%
5 3
 
< 0.1%

본번
Real number (ℝ)

Distinct1045
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean403.5774
Minimum1
Maximum1711
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:47.731602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37
Q1189
median368
Q3571
95-th percentile943.05
Maximum1711
Range1710
Interquartile range (IQR)382

Descriptive statistics

Standard deviation278.30453
Coefficient of variation (CV)0.68959394
Kurtosis0.65893332
Mean403.5774
Median Absolute Deviation (MAD)190
Skewness0.87345249
Sum4035774
Variance77453.41
MonotonicityNot monotonic
2023-12-13T01:28:47.959560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
397 133
 
1.3%
587 95
 
0.9%
392 94
 
0.9%
589 91
 
0.9%
893 81
 
0.8%
230 81
 
0.8%
588 64
 
0.6%
560 47
 
0.5%
584 46
 
0.5%
549 43
 
0.4%
Other values (1035) 9225
92.2%
ValueCountFrequency (%)
1 15
0.1%
2 23
0.2%
3 31
0.3%
4 13
0.1%
5 25
0.2%
6 6
 
0.1%
7 14
0.1%
8 18
0.2%
9 19
0.2%
10 20
0.2%
ValueCountFrequency (%)
1711 2
 
< 0.1%
1710 1
 
< 0.1%
1698 1
 
< 0.1%
1670 3
 
< 0.1%
1663 1
 
< 0.1%
1638 3
 
< 0.1%
1637 1
 
< 0.1%
1635 2
 
< 0.1%
1372 12
0.1%
1370 3
 
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct87
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1827
Minimum0
Maximum219
Zeros3667
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:48.155129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile19
Maximum219
Range219
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.9857745
Coefficient of variation (CV)2.3873992
Kurtosis98.006534
Mean4.1827
Median Absolute Deviation (MAD)1
Skewness7.7219307
Sum41827
Variance99.715692
MonotonicityNot monotonic
2023-12-13T01:28:48.313718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3667
36.7%
1 1876
18.8%
2 933
 
9.3%
3 745
 
7.4%
4 446
 
4.5%
5 399
 
4.0%
7 266
 
2.7%
6 256
 
2.6%
8 153
 
1.5%
11 142
 
1.4%
Other values (77) 1117
 
11.2%
ValueCountFrequency (%)
0 3667
36.7%
1 1876
18.8%
2 933
 
9.3%
3 745
 
7.4%
4 446
 
4.5%
5 399
 
4.0%
6 256
 
2.6%
7 266
 
2.7%
8 153
 
1.5%
9 137
 
1.4%
ValueCountFrequency (%)
219 1
 
< 0.1%
209 2
 
< 0.1%
153 1
 
< 0.1%
118 9
0.1%
107 2
 
< 0.1%
103 3
 
< 0.1%
102 3
 
< 0.1%
101 3
 
< 0.1%
99 1
 
< 0.1%
97 1
 
< 0.1%

동
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8189 
1
1334 
2
 
153
3
 
65
4
 
44
Other values (33)
 
215

Length

Max length4
Median length1
Mean length1.0248
Min length1

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8189
81.9%
1 1334
 
13.3%
2 153
 
1.5%
3 65
 
0.7%
4 44
 
0.4%
8001 40
 
0.4%
7 26
 
0.3%
5 20
 
0.2%
6 20
 
0.2%
8 15
 
0.1%
Other values (28) 94
 
0.9%

Length

2023-12-13T01:28:48.480991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 8189
81.9%
1 1334
 
13.3%
2 153
 
1.5%
3 65
 
0.7%
4 44
 
0.4%
8001 40
 
0.4%
7 26
 
0.3%
5 20
 
0.2%
6 20
 
0.2%
8 15
 
0.1%
Other values (28) 94
 
0.9%

호
Text

Distinct392
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:28:48.741184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0262
Min length1

Characters and Unicode

Total characters30262
Distinct characters23
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

Unique257 ?
Unique (%)2.6%

Sample

1st row101
2nd row301
3rd row101
4th row104
5th row102
ValueCountFrequency (%)
101 4240
42.4%
102 1677
 
16.8%
103 735
 
7.3%
201 676
 
6.8%
104 364
 
3.6%
301 217
 
2.2%
105 215
 
2.1%
8101 171
 
1.7%
106 128
 
1.3%
401 103
 
1.0%
Other values (382) 1474
 
14.7%
2023-12-13T01:28:49.124236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14034
46.4%
0 9578
31.7%
2 2990
 
9.9%
3 1317
 
4.4%
4 738
 
2.4%
5 484
 
1.6%
8 359
 
1.2%
6 310
 
1.0%
7 199
 
0.7%
9 128
 
0.4%
Other values (13) 125
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30137
99.6%
Dash Punctuation 63
 
0.2%
Uppercase Letter 46
 
0.2%
Other Letter 13
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14034
46.6%
0 9578
31.8%
2 2990
 
9.9%
3 1317
 
4.4%
4 738
 
2.4%
5 484
 
1.6%
8 359
 
1.2%
6 310
 
1.0%
7 199
 
0.7%
9 128
 
0.4%
Other Letter
ValueCountFrequency (%)
부 3
23.1%
가 2
15.4%
화 2
15.4%
실 2
15.4%
장 2
15.4%
동 1
 
7.7%
설 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 36
78.3%
B 8
 
17.4%
C 2
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
66.7%
b 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30200
99.8%
Latin 49
 
0.2%
Hangul 13
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14034
46.5%
0 9578
31.7%
2 2990
 
9.9%
3 1317
 
4.4%
4 738
 
2.4%
5 484
 
1.6%
8 359
 
1.2%
6 310
 
1.0%
7 199
 
0.7%
9 128
 
0.4%
Hangul
ValueCountFrequency (%)
부 3
23.1%
가 2
15.4%
화 2
15.4%
실 2
15.4%
장 2
15.4%
동 1
 
7.7%
설 1
 
7.7%
Latin
ValueCountFrequency (%)
A 36
73.5%
B 8
 
16.3%
a 2
 
4.1%
C 2
 
4.1%
b 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30249
> 99.9%
Hangul 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14034
46.4%
0 9578
31.7%
2 2990
 
9.9%
3 1317
 
4.4%
4 738
 
2.4%
5 484
 
1.6%
8 359
 
1.2%
6 310
 
1.0%
7 199
 
0.7%
9 128
 
0.4%
Other values (6) 112
 
0.4%
Hangul
ValueCountFrequency (%)
부 3
23.1%
가 2
15.4%
화 2
15.4%
실 2
15.4%
장 2
15.4%
동 1
 
7.7%
설 1
 
7.7%

물건지
Text

Distinct9291
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:28:49.463355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length26.4694
Min length19

Characters and Unicode

Total characters264694
Distinct characters166
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8803 ?
Unique (%)88.0%

Sample

1st row충청남도 홍성군 갈산면 가곡리 산 74-1 101호
2nd row[ 충절로 1050 ] 0000동 0301호
3rd row충청남도 홍성군 결성면 금곡리 683-9 101호
4th row충청남도 홍성군 광천읍 신진리 605 104호
5th row충청남도 홍성군 갈산면 부기리 426-3 102호
ValueCountFrequency (%)
6944
 
11.3%
충청남도 6528
 
10.6%
홍성군 6528
 
10.6%
0000동 3082
 
5.0%
101호 2977
 
4.8%
102호 1276
 
2.1%
0101호 1263
 
2.1%
홍성읍 1163
 
1.9%
1동 1010
 
1.6%
광천읍 860
 
1.4%
Other values (4558) 29871
48.6%
2023-12-13T01:28:49.957063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51502
19.5%
0 29033
 
11.0%
1 22837
 
8.6%
호 10141
 
3.8%
홍 9553
 
3.6%
성 8533
 
3.2%
2 8335
 
3.1%
남 7356
 
2.8%
청 7073
 
2.7%
충 7023
 
2.7%
Other values (156) 103308
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114241
43.2%
Decimal Number 86662
32.7%
Space Separator 51502
19.5%
Dash Punctuation 5290
 
2.0%
Close Punctuation 3472
 
1.3%
Open Punctuation 3472
 
1.3%
Uppercase Letter 52
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 10141
 
8.9%
홍 9553
 
8.4%
성 8533
 
7.5%
남 7356
 
6.4%
청 7073
 
6.2%
충 7023
 
6.1%
도 6601
 
5.8%
군 6528
 
5.7%
리 6528
 
5.7%
동 5716
 
5.0%
Other values (136) 39189
34.3%
Decimal Number
ValueCountFrequency (%)
0 29033
33.5%
1 22837
26.4%
2 8335
 
9.6%
3 6073
 
7.0%
4 4756
 
5.5%
5 4003
 
4.6%
6 3370
 
3.9%
7 2892
 
3.3%
8 2800
 
3.2%
9 2563
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
A 36
69.2%
B 11
 
21.2%
L 3
 
5.8%
C 2
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
a 2
66.7%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
51502
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5290
100.0%
Close Punctuation
ValueCountFrequency (%)
] 3472
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150398
56.8%
Hangul 114241
43.2%
Latin 55
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 10141
 
8.9%
홍 9553
 
8.4%
성 8533
 
7.5%
남 7356
 
6.4%
청 7073
 
6.2%
충 7023
 
6.1%
도 6601
 
5.8%
군 6528
 
5.7%
리 6528
 
5.7%
동 5716
 
5.0%
Other values (136) 39189
34.3%
Common
ValueCountFrequency (%)
51502
34.2%
0 29033
19.3%
1 22837
15.2%
2 8335
 
5.5%
3 6073
 
4.0%
- 5290
 
3.5%
4 4756
 
3.2%
5 4003
 
2.7%
] 3472
 
2.3%
[ 3472
 
2.3%
Other values (4) 11625
 
7.7%
Latin
ValueCountFrequency (%)
A 36
65.5%
B 11
 
20.0%
L 3
 
5.5%
a 2
 
3.6%
C 2
 
3.6%
b 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150453
56.8%
Hangul 114241
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51502
34.2%
0 29033
19.3%
1 22837
15.2%
2 8335
 
5.5%
3 6073
 
4.0%
- 5290
 
3.5%
4 4756
 
3.2%
5 4003
 
2.7%
] 3472
 
2.3%
[ 3472
 
2.3%
Other values (10) 11680
 
7.8%
Hangul
ValueCountFrequency (%)
호 10141
 
8.9%
홍 9553
 
8.4%
성 8533
 
7.5%
남 7356
 
6.4%
청 7073
 
6.2%
충 7023
 
6.1%
도 6601
 
5.8%
군 6528
 
5.7%
리 6528
 
5.7%
동 5716
 
5.0%
Other values (136) 39189
34.3%

시가표준액
Real number (ℝ)

Distinct8278
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58475940
Minimum10800
Maximum5.3719725 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:50.103641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10800
5-th percentile392950
Q11526400
median9376850
Q352499580
95-th percentile2.3286775 × 108
Maximum5.3719725 × 109
Range5.3719617 × 109
Interquartile range (IQR)50973180

Descriptive statistics

Standard deviation1.7805632 × 108
Coefficient of variation (CV)3.04495
Kurtosis199.6484
Mean58475940
Median Absolute Deviation (MAD)8833225
Skewness11.232123
Sum5.847594 × 1011
Variance3.1704051 × 1016
MonotonicityNot monotonic
2023-12-13T01:28:50.263441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
882000 26
 
0.3%
990000 24
 
0.2%
39312050 20
 
0.2%
489600 20
 
0.2%
972000 19
 
0.2%
633600 18
 
0.2%
38123020 18
 
0.2%
1980000 17
 
0.2%
561600 17
 
0.2%
1200000 16
 
0.2%
Other values (8268) 9805
98.0%
ValueCountFrequency (%)
10800 1
< 0.1%
16500 1
< 0.1%
20000 1
< 0.1%
21850 1
< 0.1%
22100 1
< 0.1%
28800 1
< 0.1%
31050 1
< 0.1%
31900 1
< 0.1%
32000 1
< 0.1%
33100 1
< 0.1%
ValueCountFrequency (%)
5371972470 1
< 0.1%
4446514770 1
< 0.1%
3865515360 1
< 0.1%
2916711640 1
< 0.1%
2862707400 1
< 0.1%
2557269480 1
< 0.1%
2427652810 1
< 0.1%
2397986890 1
< 0.1%
2389002910 1
< 0.1%
2348849010 1
< 0.1%

연면적
Real number (ℝ)

Distinct6238
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228.13219
Minimum0.33
Maximum11504.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:28:50.434003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.33
5-th percentile17.28
Q151.6075
median119.97
Q3237.7825
95-th percentile812.5775
Maximum11504.51
Range11504.18
Interquartile range (IQR)186.175

Descriptive statistics

Standard deviation418.30177
Coefficient of variation (CV)1.8335938
Kurtosis119.50841
Mean228.13219
Median Absolute Deviation (MAD)78.265
Skewness8.2139432
Sum2281321.9
Variance174976.37
MonotonicityNot monotonic
2023-12-13T01:28:50.896631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 293
 
2.9%
198.0 60
 
0.6%
27.0 44
 
0.4%
36.0 29
 
0.3%
12.0 28
 
0.3%
330.0 28
 
0.3%
144.0 27
 
0.3%
96.0 27
 
0.3%
240.0 26
 
0.3%
192.0 25
 
0.2%
Other values (6228) 9413
94.1%
ValueCountFrequency (%)
0.33 1
 
< 0.1%
1.21 1
 
< 0.1%
1.233 1
 
< 0.1%
1.26 1
 
< 0.1%
1.8 1
 
< 0.1%
2.16 2
 
< 0.1%
2.28 1
 
< 0.1%
2.52 1
 
< 0.1%
2.73 1
 
< 0.1%
3.0 5
0.1%
ValueCountFrequency (%)
11504.51 1
< 0.1%
7576.83 1
< 0.1%
7026.03 1
< 0.1%
6979.76 1
< 0.1%
6580.0 1
< 0.1%
6271.53 1
< 0.1%
6162.0 1
< 0.1%
5916.2508 1
< 0.1%
5860.0 1
< 0.1%
5591.26 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20210601
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210601
2nd row20210601
3rd row20210601
4th row20210601
5th row20210601

Common Values

ValueCountFrequency (%)
20210601 10000
100.0%

Length

2023-12-13T01:28:51.031209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:28:51.118936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210601 10000
100.0%

Interactions

2023-12-13T01:28:44.788618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:40.807533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.532779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.284715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.339406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.072391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.917313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:40.921209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.653879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.422727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.458035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.190864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:45.053395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.054185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.769967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.545012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.577356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.312446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:45.155704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.186954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.893934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.671915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.696888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.435822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:45.254625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.287710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.041180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.769839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.835584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.528584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:45.388054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:41.405447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:42.151536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.223605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:43.963323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:28:44.655810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:28:51.189903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리특수지본번부번동시가표준액연면적
법정동1.0000.3980.0430.2840.0820.1950.0410.029
법정리0.3981.0000.0800.4880.1530.1800.0120.077
특수지0.0430.0801.0000.2180.0000.0000.0790.000
본번0.2840.4880.2181.0000.0710.5400.1240.094
부번0.0820.1530.0000.0711.0000.2020.0340.000
동0.1950.1800.0000.5400.2021.0000.1150.059
시가표준액0.0410.0120.0790.1240.0340.1151.0000.816
연면적0.0290.0770.0000.0940.0000.0590.8161.000
2023-12-13T01:28:51.321939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동특수지
동1.0000.000
특수지0.0001.000
2023-12-13T01:28:51.439892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리본번부번시가표준액연면적특수지동
법정동1.0000.229-0.118-0.059-0.2840.0480.0240.073
법정리0.2291.000-0.018-0.066-0.1250.0680.0660.064
본번-0.118-0.0181.000-0.2360.2550.0290.1330.219
부번-0.059-0.066-0.2361.000-0.055-0.0300.0000.079
시가표준액-0.284-0.1250.255-0.0551.0000.4650.0340.042
연면적0.0480.0680.029-0.0300.4651.0000.0000.023
특수지0.0240.0660.1330.0000.0340.0001.0000.000
동0.0730.0640.2190.0790.0420.0230.0001.000

Missing values

2023-12-13T01:28:45.582130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:28:45.854508image/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
30962충청남도홍성군4480020213802427410101충청남도 홍성군 갈산면 가곡리 산 74-1 101호1200000240.020210601
9충청남도홍성군44800202125021137500301[ 충절로 1050 ] 0000동 0301호321167860574.5420210601
23653충청남도홍성군44800202136024168390101충청남도 홍성군 결성면 금곡리 683-9 101호880000176.020210601
7556충청남도홍성군44800202125321160500104충청남도 홍성군 광천읍 신진리 605 104호45076500135.020210601
30167충청남도홍성군44800202138030142630102충청남도 홍성군 갈산면 부기리 426-3 102호6017760089.5520210601
15380충청남도홍성군44800202133021121900101[ 홍장남로672번길 16 ] 0000동 0101호56454300108.1520210601
2419충청남도홍성군44800202133029161200101[ 충절로 586-8 ] 0000동 0101호69468730160.1420210601
12015충청남도홍성군44800202125026121210102충청남도 홍성군 홍성읍 남장리 212-1 102호1446326070.2120210601
4895충청남도홍성군448002021250301104208001A-110[ 조양로247번길 9 ] 8001동 A-110호69013606.9120210601
29385충청남도홍성군4480020213802311060102충청남도 홍성군 갈산면 신안리 10-6 102호1161800232.3620210601
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자
7243충청남도홍성군4480020212502617410105충청남도 홍성군 홍성읍 남장리 74-1 105호666503039.1620210601
8892충청남도홍성군44800202125321153130101충청남도 홍성군 광천읍 신진리 531-3 101호9360000180.020210601
12497충청남도홍성군44800202125023136530102충청남도 홍성군 홍성읍 소향리 365-3 102호1306110059.120210601
1540충청남도홍성군4480020213602417551101[ 구성남로 158-30 ] 0001동 0101호787437201789.6320210601
13347충청남도홍성군44800202125026134710101충청남도 홍성군 홍성읍 남장리 347-1 101호45160500105.020210601
4961충청남도홍성군448002021253211394140103충청남도 홍성군 광천읍 신진리 394-14 103호543600036.020210601
4928충청남도홍성군448002021250311409110201충청남도 홍성군 홍성읍 내법리 409-11 201호330741880461.9320210601
9955충청남도홍성군44800202125022162600404[ 의사로52번길 15-3 ] 0000동 0404호85375080137.4820210601
27326충청남도홍성군44800202133023119840102충청남도 홍성군 홍동면 원천리 198-4 102호79200072.020210601
24996충청남도홍성군44800202133023119950103충청남도 홍성군 홍동면 원천리 199-5 103호720000144.020210601

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적기준일자# duplicates
16충청남도홍성군44800202139025137921101충청남도 홍성군 구항면 장양리 379-2 1동 101호22148000196.0202106015
5충청남도홍성군44800202132031187500101충청남도 홍성군 금마면 죽림리 875 101호15288000392.0202106013
7충청남도홍성군44800202135024126610101충청남도 홍성군 은하면 대율리 266-1 101호469200019.55202106013
10충청남도홍성군4480020213602417551101[ 구성남로 158-30 ] 0001동 0101호787437201789.63202106013
0충청남도홍성군44800202125622128330101충청남도 홍성군 홍북읍 상하리 283-3 101호1098240052.8202106012
1충청남도홍성군448002021256241327181101충청남도 홍성군 홍북읍 내덕리 327-18 1동 101호121500001012.5202106012
2충청남도홍성군44800202125624170531101충청남도 홍성군 홍북읍 내덕리 705-3 1동 101호1980000396.0202106012
3충청남도홍성군448002021256251167000101충청남도 홍성군 홍북읍 신경리 1670 101호399600027.0202106012
4충청남도홍성군44800202125629121901101충청남도 홍성군 홍북읍 갈산리 219 1동 101호16600033.2202106012
6충청남도홍성군44800202132032125401101충청남도 홍성군 금마면 화양리 254 1동 101호95347140332.22202106012