Overview

Dataset statistics

Number of variables15
Number of observations2025
Missing cells9
Missing cells (%)< 0.1%
Duplicate rows216
Duplicate rows (%)10.7%
Total size in memory259.2 KiB
Average record size in memory131.1 B

Variable types

Categorical5
Numeric8
Text1
DateTime1

Dataset

Description경상북도 울진군 일반건축물 시가표준액에 대한 데이더로 일반건축물에 대한 지방세 부과기준인 시가표준액 등을 제공합니다.
URLhttps://www.data.go.kr/data/15079946/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
과세연도 has constant value ""Constant
기준일자 has constant value ""Constant
Dataset has 216 (10.7%) duplicate rowsDuplicates
법정동 is highly overall correlated with 본번 and 1 other fieldsHigh correlation
법정리 is highly overall correlated with 특수지High correlation
본번 is highly overall correlated with 법정동High correlation
부번 is highly overall correlated with 법정동High correlation
건물동 is highly overall correlated with 특수지High correlation
건물시가표준액 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
연면적 is highly overall correlated with 건물시가표준액High correlation
특수지 is highly overall correlated with 법정리 and 2 other fieldsHigh correlation
특수지 is highly imbalanced (96.3%)Imbalance
부번 has 740 (36.5%) zerosZeros
건물동 has 37 (1.8%) zerosZeros
건물시가표준액 has 39 (1.9%) zerosZeros
연면적 has 48 (2.4%) zerosZeros

Reproduction

Analysis started2023-12-12 14:07:51.512172
Analysis finished2023-12-12 14:08:00.245282
Duration8.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
경상북도
2025 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 2025
100.0%

Length

2023-12-12T23:08:00.320925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:00.443611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 2025
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
울진군
2025 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울진군 2025
100.0%

Length

2023-12-12T23:08:00.549834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:00.661814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울진군 2025
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
47930
2025 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47930
2nd row47930
3rd row47930
4th row47930
5th row47930

Common Values

ValueCountFrequency (%)
47930 2025
100.0%

Length

2023-12-12T23:08:00.773094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:00.899114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47930 2025
100.0%

과세연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
2022
2025 

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 2025
100.0%

Length

2023-12-12T23:08:01.019546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:01.116336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 2025
100.0%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean289.70765
Minimum250
Maximum400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:01.209032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile250
Q1250
median250
Q3360
95-th percentile370
Maximum400
Range150
Interquartile range (IQR)110

Descriptive statistics

Standard deviation53.523714
Coefficient of variation (CV)0.18475078
Kurtosis-1.5173817
Mean289.70765
Median Absolute Deviation (MAD)0
Skewness0.64484538
Sum586658
Variance2864.788
MonotonicityNot monotonic
2023-12-12T23:08:01.322415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
250 1280
63.2%
360 583
28.8%
380 54
 
2.7%
370 36
 
1.8%
310 32
 
1.6%
253 16
 
0.8%
400 13
 
0.6%
330 6
 
0.3%
350 4
 
0.2%
390 1
 
< 0.1%
ValueCountFrequency (%)
250 1280
63.2%
253 16
 
0.8%
310 32
 
1.6%
330 6
 
0.3%
350 4
 
0.2%
360 583
28.8%
370 36
 
1.8%
380 54
 
2.7%
390 1
 
< 0.1%
400 13
 
0.6%
ValueCountFrequency (%)
400 13
 
0.6%
390 1
 
< 0.1%
380 54
 
2.7%
370 36
 
1.8%
360 583
28.8%
350 4
 
0.2%
330 6
 
0.3%
310 32
 
1.6%
253 16
 
0.8%
250 1280
63.2%

법정리
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.195062
Minimum21
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:01.433593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile21
Q121
median21
Q321
95-th percentile22
Maximum33
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.98304566
Coefficient of variation (CV)0.046380882
Kurtosis86.207573
Mean21.195062
Median Absolute Deviation (MAD)0
Skewness8.5290567
Sum42920
Variance0.96637876
MonotonicityNot monotonic
2023-12-12T23:08:01.584947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
21 1855
91.6%
22 89
 
4.4%
23 54
 
2.7%
33 6
 
0.3%
26 5
 
0.2%
25 4
 
0.2%
27 4
 
0.2%
31 4
 
0.2%
24 2
 
0.1%
28 1
 
< 0.1%
ValueCountFrequency (%)
21 1855
91.6%
22 89
 
4.4%
23 54
 
2.7%
24 2
 
0.1%
25 4
 
0.2%
26 5
 
0.2%
27 4
 
0.2%
28 1
 
< 0.1%
29 1
 
< 0.1%
31 4
 
0.2%
ValueCountFrequency (%)
33 6
 
0.3%
31 4
 
0.2%
29 1
 
< 0.1%
28 1
 
< 0.1%
27 4
 
0.2%
26 5
 
0.2%
25 4
 
0.2%
24 2
 
0.1%
23 54
2.7%
22 89
4.4%

특수지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
1
2017 
2
 
8

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 2017
99.6%
2 8
 
0.4%

Length

2023-12-12T23:08:01.709945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:08:01.824063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2017
99.6%
2 8
 
0.4%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct244
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean575.63358
Minimum1
Maximum1465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:01.983018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile42.4
Q1122
median311
Q31438
95-th percentile1438
Maximum1465
Range1464
Interquartile range (IQR)1316

Descriptive statistics

Standard deviation547.70829
Coefficient of variation (CV)0.95148773
Kurtosis-1.1410897
Mean575.63358
Median Absolute Deviation (MAD)229
Skewness0.74237308
Sum1165658
Variance299984.37
MonotonicityNot monotonic
2023-12-12T23:08:02.180002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438 523
25.8%
82 66
 
3.3%
968 60
 
3.0%
1 43
 
2.1%
302 39
 
1.9%
205 39
 
1.9%
60 32
 
1.6%
194 30
 
1.5%
196 25
 
1.2%
513 21
 
1.0%
Other values (234) 1147
56.6%
ValueCountFrequency (%)
1 43
2.1%
2 6
 
0.3%
3 2
 
0.1%
9 1
 
< 0.1%
12 1
 
< 0.1%
14 3
 
0.1%
19 4
 
0.2%
20 6
 
0.3%
29 6
 
0.3%
30 4
 
0.2%
ValueCountFrequency (%)
1465 3
 
0.1%
1438 523
25.8%
1036 1
 
< 0.1%
968 60
 
3.0%
914 4
 
0.2%
886 6
 
0.3%
630 2
 
0.1%
590 1
 
< 0.1%
582 2
 
0.1%
581 4
 
0.2%

부번
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3980247
Minimum0
Maximum127
Zeros740
Zeros (%)36.5%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:02.385943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile16
Maximum127
Range127
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.7749723
Coefficient of variation (CV)1.7678328
Kurtosis59.566797
Mean4.3980247
Median Absolute Deviation (MAD)2
Skewness5.7297112
Sum8906
Variance60.450194
MonotonicityNot monotonic
2023-12-12T23:08:02.597698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 740
36.5%
1 226
 
11.2%
5 192
 
9.5%
2 169
 
8.3%
3 122
 
6.0%
4 98
 
4.8%
6 67
 
3.3%
8 50
 
2.5%
9 47
 
2.3%
10 37
 
1.8%
Other values (30) 277
 
13.7%
ValueCountFrequency (%)
0 740
36.5%
1 226
 
11.2%
2 169
 
8.3%
3 122
 
6.0%
4 98
 
4.8%
5 192
 
9.5%
6 67
 
3.3%
7 34
 
1.7%
8 50
 
2.5%
9 47
 
2.3%
ValueCountFrequency (%)
127 1
 
< 0.1%
98 1
 
< 0.1%
85 2
 
0.1%
83 1
 
< 0.1%
49 2
 
0.1%
47 1
 
< 0.1%
37 1
 
< 0.1%
36 9
0.4%
34 1
 
< 0.1%
30 3
 
0.1%

건물동
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)1.1%
Missing9
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.9707341
Minimum0
Maximum127
Zeros37
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:02.727244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum127
Range127
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.8969639
Coefficient of variation (CV)4.514543
Kurtosis133.10119
Mean1.9707341
Median Absolute Deviation (MAD)0
Skewness11.430779
Sum3973
Variance79.155967
MonotonicityNot monotonic
2023-12-12T23:08:02.841374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1792
88.5%
2 109
 
5.4%
0 37
 
1.8%
3 19
 
0.9%
4 12
 
0.6%
6 9
 
0.4%
7 8
 
0.4%
30 4
 
0.2%
101 4
 
0.2%
104 3
 
0.1%
Other values (12) 19
 
0.9%
(Missing) 9
 
0.4%
ValueCountFrequency (%)
0 37
 
1.8%
1 1792
88.5%
2 109
 
5.4%
3 19
 
0.9%
4 12
 
0.6%
5 2
 
0.1%
6 9
 
0.4%
7 8
 
0.4%
8 3
 
0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
127 1
 
< 0.1%
124 1
 
< 0.1%
106 2
0.1%
104 3
0.1%
102 3
0.1%
101 4
0.2%
30 4
0.2%
20 1
 
< 0.1%
17 1
 
< 0.1%
16 2
0.1%

건물호
Real number (ℝ)

Distinct115
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean669.79012
Minimum0
Maximum9999
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:02.978940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile101
Q1101
median201
Q3301
95-th percentile8101
Maximum9999
Range9999
Interquartile range (IQR)200

Descriptive statistics

Standard deviation1966.9257
Coefficient of variation (CV)2.9366299
Kurtosis14.074517
Mean669.79012
Median Absolute Deviation (MAD)100
Skewness3.9678264
Sum1356325
Variance3868796.6
MonotonicityNot monotonic
2023-12-12T23:08:03.109469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101 526
26.0%
201 262
 
12.9%
102 179
 
8.8%
301 98
 
4.8%
103 73
 
3.6%
8101 46
 
2.3%
202 46
 
2.3%
9999 39
 
1.9%
401 29
 
1.4%
203 26
 
1.3%
Other values (105) 701
34.6%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 25
1.2%
2 10
 
0.5%
3 4
 
0.2%
4 2
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 2
 
0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
9999 39
1.9%
8202 2
 
0.1%
8201 2
 
0.1%
8106 2
 
0.1%
8105 2
 
0.1%
8104 3
 
0.1%
8103 3
 
0.1%
8102 12
 
0.6%
8101 46
2.3%
801 3
 
0.1%

물건지명
Text

Distinct1321
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
2023-12-12T23:08:03.561383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length32
Mean length29.357037
Min length21

Characters and Unicode

Total characters59448
Distinct characters69
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

Unique1091 ?
Unique (%)53.9%

Sample

1st row경상북도 울진군 울진읍 읍내리 2-2 1동 101호
2nd row경상북도 울진군 울진읍 읍내리 2-3 1동 101호
3rd row경상북도 울진군 울진읍 읍내리 29-1 1동 201호
4th row경상북도 울진군 울진읍 읍내리 29-1 1동 301호
5th row경상북도 울진군 울진읍 읍내리 29-1 1동 401호
ValueCountFrequency (%)
경상북도 2025
14.3%
울진군 2025
14.3%
1동 1792
12.7%
울진읍 1280
 
9.1%
읍내리 1268
 
9.0%
온정면 583
 
4.1%
101호 526
 
3.7%
1438 523
 
3.7%
소태리 523
 
3.7%
201호 262
 
1.9%
Other values (645) 3329
23.5%
2023-12-12T23:08:04.133375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12111
20.4%
1 5415
 
9.1%
울 3305
 
5.6%
진 3305
 
5.6%
읍 2564
 
4.3%
0 2086
 
3.5%
북 2057
 
3.5%
도 2027
 
3.4%
경 2025
 
3.4%
군 2025
 
3.4%
Other values (59) 22528
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30305
51.0%
Decimal Number 15747
26.5%
Space Separator 12111
 
20.4%
Dash Punctuation 1285
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
울 3305
10.9%
진 3305
10.9%
읍 2564
 
8.5%
북 2057
 
6.8%
도 2027
 
6.7%
경 2025
 
6.7%
군 2025
 
6.7%
상 2025
 
6.7%
리 2025
 
6.7%
호 2024
 
6.7%
Other values (47) 6923
22.8%
Decimal Number
ValueCountFrequency (%)
1 5415
34.4%
0 2086
 
13.2%
2 1901
 
12.1%
3 1717
 
10.9%
4 1269
 
8.1%
8 1097
 
7.0%
5 853
 
5.4%
9 581
 
3.7%
6 541
 
3.4%
7 287
 
1.8%
Space Separator
ValueCountFrequency (%)
12111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30305
51.0%
Common 29143
49.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
울 3305
10.9%
진 3305
10.9%
읍 2564
 
8.5%
북 2057
 
6.8%
도 2027
 
6.7%
경 2025
 
6.7%
군 2025
 
6.7%
상 2025
 
6.7%
리 2025
 
6.7%
호 2024
 
6.7%
Other values (47) 6923
22.8%
Common
ValueCountFrequency (%)
12111
41.6%
1 5415
18.6%
0 2086
 
7.2%
2 1901
 
6.5%
3 1717
 
5.9%
- 1285
 
4.4%
4 1269
 
4.4%
8 1097
 
3.8%
5 853
 
2.9%
9 581
 
2.0%
Other values (2) 828
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30305
51.0%
ASCII 29143
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12111
41.6%
1 5415
18.6%
0 2086
 
7.2%
2 1901
 
6.5%
3 1717
 
5.9%
- 1285
 
4.4%
4 1269
 
4.4%
8 1097
 
3.8%
5 853
 
2.9%
9 581
 
2.0%
Other values (2) 828
 
2.8%
Hangul
ValueCountFrequency (%)
울 3305
10.9%
진 3305
10.9%
읍 2564
 
8.5%
북 2057
 
6.8%
도 2027
 
6.7%
경 2025
 
6.7%
군 2025
 
6.7%
상 2025
 
6.7%
리 2025
 
6.7%
호 2024
 
6.7%
Other values (47) 6923
22.8%

건물시가표준액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1162
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52081328
Minimum0
Maximum3.3725704 × 109
Zeros39
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:04.274725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1539138.8
Q114251380
median22937100
Q352056000
95-th percentile1.6634126 × 108
Maximum3.3725704 × 109
Range3.3725704 × 109
Interquartile range (IQR)37804620

Descriptive statistics

Standard deviation1.252246 × 108
Coefficient of variation (CV)2.4044048
Kurtosis375.76704
Mean52081328
Median Absolute Deviation (MAD)15781570
Skewness16.193108
Sum1.0546469 × 1011
Variance1.5681199 × 1016
MonotonicityNot monotonic
2023-12-12T23:08:04.410500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22937100 502
 
24.8%
0 39
 
1.9%
45874200 17
 
0.8%
7110965 14
 
0.7%
15920100 9
 
0.4%
5370470 7
 
0.3%
1949900 7
 
0.3%
10939950 7
 
0.3%
163344000 6
 
0.3%
6892167 6
 
0.3%
Other values (1152) 1411
69.7%
ValueCountFrequency (%)
0 39
1.9%
99738 1
 
< 0.1%
113100 1
 
< 0.1%
120000 1
 
< 0.1%
136080 1
 
< 0.1%
199680 1
 
< 0.1%
202020 1
 
< 0.1%
220320 1
 
< 0.1%
288000 1
 
< 0.1%
320250 1
 
< 0.1%
ValueCountFrequency (%)
3372570422 1
< 0.1%
2860840992 1
< 0.1%
1257222721 1
< 0.1%
881469917 1
< 0.1%
778479572 1
< 0.1%
716542370 1
< 0.1%
681791880 1
< 0.1%
609000000 1
< 0.1%
592418024 1
< 0.1%
590604532 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct995
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.57994
Minimum0
Maximum4806.27
Zeros48
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-12T23:08:04.560602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.53
Q154.57
median75.7
Q3132.326
95-th percentile341.77
Maximum4806.27
Range4806.27
Interquartile range (IQR)77.756

Descriptive statistics

Standard deviation178.53138
Coefficient of variation (CV)1.480606
Kurtosis247.79173
Mean120.57994
Median Absolute Deviation (MAD)33.22
Skewness11.408256
Sum244174.37
Variance31873.453
MonotonicityNot monotonic
2023-12-12T23:08:04.719736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.7 502
 
24.8%
0.0 48
 
2.4%
151.4 17
 
0.8%
13.65 15
 
0.7%
18.0 12
 
0.6%
21.0 10
 
0.5%
64.98 9
 
0.4%
226.48 9
 
0.4%
266.49 8
 
0.4%
168.87 8
 
0.4%
Other values (985) 1387
68.5%
ValueCountFrequency (%)
0.0 48
2.4%
1.04 1
 
< 0.1%
1.08 1
 
< 0.1%
1.47 1
 
< 0.1%
2.4 1
 
< 0.1%
2.52 1
 
< 0.1%
2.88 2
 
0.1%
3.12 1
 
< 0.1%
4.32 1
 
< 0.1%
4.62 6
 
0.3%
ValueCountFrequency (%)
4806.27 1
< 0.1%
1916.03 1
< 0.1%
1808.91 1
< 0.1%
1284.65 1
< 0.1%
1242.0 2
0.1%
985.22 1
< 0.1%
963.48 2
0.1%
923.65 2
0.1%
840.0 1
< 0.1%
815.02 2
0.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
Minimum2022-06-01 00:00:00
Maximum2022-06-01 00:00:00
2023-12-12T23:08:04.836893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:08:04.935544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:07:58.733459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:52.346972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.601775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.519448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.402737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.221223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.001735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.893575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.815878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:52.465710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.722496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.647595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.495515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.314504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.126264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.007232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.910362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:52.579265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.860251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.760092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.595030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.411800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.222106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.119145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.993992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:52.714143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.993328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.886487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.690926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.500276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.343132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.232252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:59.083588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:52.830457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.107467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.998897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.784915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.619176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.469471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.333396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:59.172212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.248300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.212437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.127926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.884771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.707416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.588923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.432888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:59.257092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.344567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.303099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.216202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.990424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.794728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.687244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.540113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:59.349163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:53.484566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:54.410506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:55.318739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.116291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:56.894558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:57.790529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:07:58.641890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:08:05.004589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리특수지본번부번건물동건물호건물시가표준액연면적
법정동1.0000.7480.4530.8660.4300.3560.0000.2420.168
법정리0.7481.0000.5700.2490.0000.6520.0000.4880.000
특수지0.4530.5701.0000.1050.000NaN0.0000.7150.000
본번0.8660.2490.1051.0000.1790.3210.4150.0000.296
부번0.4300.0000.0000.1791.0000.0000.1090.0000.000
건물동0.3560.652NaN0.3210.0001.0000.0000.2480.143
건물호0.0000.0000.0000.4150.1090.0001.0000.0000.014
건물시가표준액0.2420.4880.7150.0000.0000.2480.0001.0000.575
연면적0.1680.0000.0000.2960.0000.1430.0140.5751.000
2023-12-12T23:08:05.135089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리본번부번건물동건물호건물시가표준액연면적특수지
법정동1.0000.3730.580-0.576-0.0950.439-0.110-0.0970.494
법정리0.3731.000-0.070-0.0030.056-0.006-0.078-0.0390.573
본번0.580-0.0701.000-0.468-0.1900.471-0.0070.0720.079
부번-0.576-0.003-0.4681.0000.015-0.377-0.0310.0190.000
건물동-0.0950.056-0.1900.0151.000-0.067-0.105-0.0881.000
건물호0.439-0.0060.471-0.377-0.0671.000-0.0150.0180.000
건물시가표준액-0.110-0.078-0.007-0.031-0.105-0.0151.0000.8180.527
연면적-0.097-0.0390.0720.019-0.0880.0180.8181.0000.000
특수지0.4940.5730.0790.0001.0000.0000.5270.0001.000

Missing values

2023-12-12T23:07:59.808683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:08:00.129927image/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

시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번건물동건물호물건지명건물시가표준액연면적기준일자
0경상북도울진군479302022250211221101경상북도 울진군 울진읍 읍내리 2-2 1동 101호222141920305.142022-06-01
1경상북도울진군479302022250211231101경상북도 울진군 울진읍 읍내리 2-3 1동 101호1973083546.752022-06-01
2경상북도울진군4793020222502112911201경상북도 울진군 울진읍 읍내리 29-1 1동 201호2536020065.72022-06-01
3경상북도울진군4793020222502112911301경상북도 울진군 울진읍 읍내리 29-1 1동 301호2536020065.72022-06-01
4경상북도울진군4793020222502112911401경상북도 울진군 울진읍 읍내리 29-1 1동 401호2536020065.72022-06-01
5경상북도울진군4793020222502112911501경상북도 울진군 울진읍 읍내리 29-1 1동 501호835704065.72022-06-01
6경상북도울진군4793020222502112912101경상북도 울진군 울진읍 읍내리 29-1 2동 101호3600222093.272022-06-01
7경상북도울진군479302022250211641901경상북도 울진군 울진읍 읍내리 64-19 1호172080021.512022-06-01
8경상북도울진군479302022250211641901경상북도 울진군 울진읍 읍내리 64-19 1호264000033.02022-06-01
9경상북도울진군47930202225021115212101경상북도 울진군 울진읍 읍내리 152-1 2동 101호1146420023.762022-06-01
시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번건물동건물호물건지명건물시가표준액연면적기준일자
2015경상북도울진군479302022250211530911경상북도 울진군 울진읍 읍내리 530-9 1동 1호1339520064.02022-06-01
2016경상북도울진군479302022250211530912경상북도 울진군 울진읍 읍내리 530-9 1동 2호1164800064.02022-06-01
2017경상북도울진군479302022250211530111101경상북도 울진군 울진읍 읍내리 530-11 1동 101호1455313446.872022-06-01
2018경상북도울진군479302022250211530151101경상북도 울진군 울진읍 읍내리 530-15 1동 101호115193567246.722022-06-01
2019경상북도울진군479302022250211530151201경상북도 울진군 울진읍 읍내리 530-15 1동 201호100168320246.722022-06-01
2020경상북도울진군479302022250211530151302경상북도 울진군 울진읍 읍내리 530-15 1동 302호202860013.82022-06-01
2021경상북도울진군479302022250211530151101경상북도 울진군 울진읍 읍내리 530-15 1동 101호115193567246.722022-06-01
2022경상북도울진군479302022250211530151201경상북도 울진군 울진읍 읍내리 530-15 1동 201호100168320246.722022-06-01
2023경상북도울진군479302022250211530151302경상북도 울진군 울진읍 읍내리 530-15 1동 302호202860013.82022-06-01
2024경상북도울진군47930202225021153101101경상북도 울진군 울진읍 읍내리 531 1동 101호347040048.22022-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세연도법정동법정리특수지본번부번건물동건물호물건지명건물시가표준액연면적기준일자# duplicates
200경상북도울진군479302022360221968519999경상북도 울진군 온정면 온정리 968-5 1동 9999호00.02022-06-0118
69경상북도울진군479302022250211216229999경상북도 울진군 울진읍 읍내리 216-2 2동 9999호00.02022-06-0114
155경상북도울진군479302022360211143801338경상북도 울진군 온정면 소태리 1438 1동 338호2293710075.72022-06-0112
176경상북도울진군479302022360211143801627경상북도 울진군 온정면 소태리 1438 1동 627호2293710075.72022-06-0112
117경상북도울진군479302022360211143801205경상북도 울진군 온정면 소태리 1438 1동 205호2293710075.72022-06-0111
121경상북도울진군479302022360211143801209경상북도 울진군 온정면 소태리 1438 1동 209호2293710075.72022-06-0111
133경상북도울진군479302022360211143801245경상북도 울진군 온정면 소태리 1438 1동 245호2293710075.72022-06-0111
141경상북도울진군479302022360211143801308경상북도 울진군 온정면 소태리 1438 1동 308호2293710075.72022-06-0111
148경상북도울진군479302022360211143801330경상북도 울진군 온정면 소태리 1438 1동 330호2293710075.72022-06-0111
156경상북도울진군479302022360211143801339경상북도 울진군 온정면 소태리 1438 1동 339호2293710075.72022-06-0111