Overview

Dataset statistics

Number of variables15
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows35
Duplicate rows (%)0.4%
Total size in memory1.3 MiB
Average record size in memory137.0 B

Variable types

Categorical6
Numeric6
Unsupported1
Text2

Dataset

Description경기도 용인시 처인구, 기흥구, 수지구 일반건축물에 대한 지방세 부과기준인 시가표준액 현황입니다. 물건지, 시가표준액, 연면적 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2021-06-01
URLhttps://www.data.go.kr/data/15080196/fileData.do

Alerts

시도명 has constant value ""Constant
과세년도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 35 (0.4%) duplicate rowsDuplicates
자치단체코드 is highly overall correlated with 법정동 and 2 other fieldsHigh correlation
시군구명 is highly overall correlated with 법정동 and 2 other fieldsHigh correlation
법정동 is highly overall correlated with 법정리 and 2 other fieldsHigh correlation
법정리 is highly overall correlated with 법정동 and 2 other fieldsHigh correlation
시가표준액 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 시가표준액High correlation
특수지 is highly imbalanced (82.7%)Imbalance
시가표준액 is highly skewed (γ1 = 20.02946803)Skewed
동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
법정리 has 4566 (45.7%) zerosZeros
부번 has 2756 (27.6%) zerosZeros

Reproduction

Analysis started2023-12-12 18:50:18.129703
Analysis finished2023-12-12 18:50:28.430517
Duration10.3 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
경기도
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 10000
100.0%

Length

2023-12-13T03:50:28.546781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:28.710495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용인시 처인구
7571 
용인시 기흥구
2429 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용인시 기흥구
2nd row용인시 처인구
3rd row용인시 처인구
4th row용인시 처인구
5th row용인시 처인구

Common Values

ValueCountFrequency (%)
용인시 처인구 7571
75.7%
용인시 기흥구 2429
 
24.3%

Length

2023-12-13T03:50:28.883708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:29.030951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 10000
50.0%
처인구 7571
37.9%
기흥구 2429
 
12.1%

자치단체코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
41461
7571 
41463
2429 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41463
2nd row41461
3rd row41461
4th row41461
5th row41461

Common Values

ValueCountFrequency (%)
41461 7571
75.7%
41463 2429
 
24.3%

Length

2023-12-13T03:50:29.225461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:29.380034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41461 7571
75.7%
41463 2429
 
24.3%

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

2023-12-13T03:50:29.544263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:29.702610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

법정동
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206.0403
Minimum101
Maximum360
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:29.850968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1104
median250
Q3259
95-th percentile360
Maximum360
Range259
Interquartile range (IQR)155

Descriptive statistics

Standard deviation98.816379
Coefficient of variation (CV)0.47959734
Kurtosis-1.5098765
Mean206.0403
Median Absolute Deviation (MAD)110
Skewness0.20704414
Sum2060403
Variance9764.6767
MonotonicityNot monotonic
2023-12-13T03:50:30.105977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
102 1150
11.5%
250 943
9.4%
253 926
9.3%
101 852
 
8.5%
256 799
 
8.0%
360 793
 
7.9%
259 716
 
7.2%
350 696
 
7.0%
340 561
 
5.6%
105 374
 
3.7%
Other values (13) 2190
21.9%
ValueCountFrequency (%)
101 852
8.5%
102 1150
11.5%
103 309
 
3.1%
104 228
 
2.3%
105 374
 
3.7%
106 298
 
3.0%
107 307
 
3.1%
108 172
 
1.7%
109 78
 
0.8%
110 73
 
0.7%
ValueCountFrequency (%)
360 793
7.9%
350 696
7.0%
340 561
5.6%
259 716
7.2%
256 799
8.0%
253 926
9.3%
250 943
9.4%
116 347
 
3.5%
115 50
 
0.5%
114 7
 
0.1%

법정리
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.6524
Minimum0
Maximum33
Zeros4566
Zeros (%)45.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:30.369399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21
Q325
95-th percentile29
Maximum33
Range33
Interquartile range (IQR)25

Descriptive statistics

Standard deviation12.710819
Coefficient of variation (CV)0.93103187
Kurtosis-1.8715443
Mean13.6524
Median Absolute Deviation (MAD)8
Skewness-0.081530638
Sum136524
Variance161.56493
MonotonicityNot monotonic
2023-12-13T03:50:30.550241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 4566
45.7%
21 733
 
7.3%
24 670
 
6.7%
23 652
 
6.5%
29 630
 
6.3%
22 613
 
6.1%
28 554
 
5.5%
27 540
 
5.4%
25 425
 
4.2%
26 309
 
3.1%
Other values (4) 308
 
3.1%
ValueCountFrequency (%)
0 4566
45.7%
21 733
 
7.3%
22 613
 
6.1%
23 652
 
6.5%
24 670
 
6.7%
25 425
 
4.2%
26 309
 
3.1%
27 540
 
5.4%
28 554
 
5.5%
29 630
 
6.3%
ValueCountFrequency (%)
33 22
 
0.2%
32 70
 
0.7%
31 102
 
1.0%
30 114
 
1.1%
29 630
6.3%
28 554
5.5%
27 540
5.4%
26 309
3.1%
25 425
4.2%
24 670
6.7%

특수지
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9475 
5
 
386
2
 
131
3
 
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 9475
94.8%
5 386
 
3.9%
2 131
 
1.3%
3 8
 
0.1%

Length

2023-12-13T03:50:30.751317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:30.948638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9475
94.8%
5 386
 
3.9%
2 131
 
1.3%
3 8
 
0.1%

본번
Real number (ℝ)

Distinct1046
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean391.1817
Minimum1
Maximum2835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:31.123317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26
Q1159
median356
Q3575
95-th percentile849
Maximum2835
Range2834
Interquartile range (IQR)416

Descriptive statistics

Standard deviation279.03332
Coefficient of variation (CV)0.71330873
Kurtosis4.2820582
Mean391.1817
Median Absolute Deviation (MAD)206
Skewness1.1832306
Sum3911817
Variance77859.594
MonotonicityNot monotonic
2023-12-13T03:50:31.361938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26 372
 
3.7%
356 169
 
1.7%
833 112
 
1.1%
254 102
 
1.0%
133 90
 
0.9%
581 79
 
0.8%
352 72
 
0.7%
1033 65
 
0.7%
829 61
 
0.6%
517 56
 
0.6%
Other values (1036) 8822
88.2%
ValueCountFrequency (%)
1 14
0.1%
2 23
0.2%
3 10
0.1%
4 13
0.1%
5 24
0.2%
6 15
0.1%
7 8
 
0.1%
8 7
 
0.1%
9 10
0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
2835 2
< 0.1%
2810 1
< 0.1%
2808 1
< 0.1%
2686 1
< 0.1%
2663 1
< 0.1%
2280 1
< 0.1%
2173 2
< 0.1%
1797 1
< 0.1%
1787 1
< 0.1%
1763 1
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct145
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.734
Minimum0
Maximum575
Zeros2756
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:31.578613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q36
95-th percentile24
Maximum575
Range575
Interquartile range (IQR)6

Descriptive statistics

Standard deviation23.618023
Coefficient of variation (CV)3.50728
Kurtosis149.68831
Mean6.734
Median Absolute Deviation (MAD)2
Skewness10.644137
Sum67340
Variance557.81103
MonotonicityNot monotonic
2023-12-13T03:50:31.814094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2756
27.6%
1 2046
20.5%
2 1003
 
10.0%
3 721
 
7.2%
6 567
 
5.7%
4 538
 
5.4%
7 458
 
4.6%
5 343
 
3.4%
8 171
 
1.7%
10 144
 
1.4%
Other values (135) 1253
12.5%
ValueCountFrequency (%)
0 2756
27.6%
1 2046
20.5%
2 1003
 
10.0%
3 721
 
7.2%
4 538
 
5.4%
5 343
 
3.4%
6 567
 
5.7%
7 458
 
4.6%
8 171
 
1.7%
9 138
 
1.4%
ValueCountFrequency (%)
575 1
 
< 0.1%
421 2
 
< 0.1%
414 1
 
< 0.1%
413 1
 
< 0.1%
370 1
 
< 0.1%
369 1
 
< 0.1%
364 5
0.1%
334 1
 
< 0.1%
333 2
 
< 0.1%
323 2
 
< 0.1%

동
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

호
Text

Distinct827
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:50:32.345836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.5525
Min length1

Characters and Unicode

Total characters25525
Distinct characters20
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

Unique489 ?
Unique (%)4.9%

Sample

1st row2073
2nd row401
3rd row101
4th row103
5th row401
ValueCountFrequency (%)
101 2116
21.2%
1 1187
 
11.9%
0 1039
 
10.4%
201 704
 
7.0%
102 617
 
6.2%
301 343
 
3.4%
2 310
 
3.1%
8101 254
 
2.5%
103 252
 
2.5%
202 158
 
1.6%
Other values (817) 3020
30.2%
2023-12-13T03:50:33.087910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10037
39.3%
0 7662
30.0%
2 2955
 
11.6%
3 1431
 
5.6%
4 961
 
3.8%
8 706
 
2.8%
5 568
 
2.2%
6 465
 
1.8%
7 343
 
1.3%
9 263
 
1.0%
Other values (10) 134
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25391
99.5%
Dash Punctuation 94
 
0.4%
Other Letter 28
 
0.1%
Uppercase Letter 11
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10037
39.5%
0 7662
30.2%
2 2955
 
11.6%
3 1431
 
5.6%
4 961
 
3.8%
8 706
 
2.8%
5 568
 
2.2%
6 465
 
1.8%
7 343
 
1.4%
9 263
 
1.0%
Other Letter
ValueCountFrequency (%)
동 24
85.7%
나 2
 
7.1%
지 1
 
3.6%
하 1
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 5
45.5%
B 3
27.3%
C 2
 
18.2%
D 1
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25486
99.8%
Hangul 28
 
0.1%
Latin 11
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10037
39.4%
0 7662
30.1%
2 2955
 
11.6%
3 1431
 
5.6%
4 961
 
3.8%
8 706
 
2.8%
5 568
 
2.2%
6 465
 
1.8%
7 343
 
1.3%
9 263
 
1.0%
Other values (2) 95
 
0.4%
Hangul
ValueCountFrequency (%)
동 24
85.7%
나 2
 
7.1%
지 1
 
3.6%
하 1
 
3.6%
Latin
ValueCountFrequency (%)
A 5
45.5%
B 3
27.3%
C 2
 
18.2%
D 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25497
99.9%
Hangul 28
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10037
39.4%
0 7662
30.1%
2 2955
 
11.6%
3 1431
 
5.6%
4 961
 
3.8%
8 706
 
2.8%
5 568
 
2.2%
6 465
 
1.8%
7 343
 
1.3%
9 263
 
1.0%
Other values (6) 106
 
0.4%
Hangul
ValueCountFrequency (%)
동 24
85.7%
나 2
 
7.1%
지 1
 
3.6%
하 1
 
3.6%

물건지
Text

Distinct9415
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T03:50:33.589875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length28.1397
Min length18

Characters and Unicode

Total characters281397
Distinct characters189
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8913 ?
Unique (%)89.1%

Sample

1st row[ 동백죽전대로 444 ] 0001동 2073호
2nd row[ 낙은로50번길 9-9 ] 0001동 0401호
3rd row[ 백옥대로2402번길 41 ] 0001동 0101호
4th row[ 금령로99번길 15 ] 0001동 0103호
5th row경기도 용인시 처인구 삼가동 470 401호
ValueCountFrequency (%)
8762
 
12.9%
경기도 5619
 
8.3%
용인시 5619
 
8.3%
처인구 4695
 
6.9%
1동 3359
 
4.9%
0001동 2898
 
4.3%
101호 1260
 
1.9%
0000동 1000
 
1.5%
기흥구 924
 
1.4%
0101호 856
 
1.3%
Other values (5387) 32941
48.5%
2023-12-13T03:50:34.371866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57934
20.6%
0 33001
 
11.7%
1 24143
 
8.6%
동 12528
 
4.5%
인 10357
 
3.7%
호 9191
 
3.3%
2 8618
 
3.1%
기 6634
 
2.4%
구 5999
 
2.1%
용 5776
 
2.1%
Other values (179) 107216
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115187
40.9%
Decimal Number 93989
33.4%
Space Separator 57934
20.6%
Dash Punctuation 4742
 
1.7%
Close Punctuation 4381
 
1.6%
Open Punctuation 4381
 
1.6%
Uppercase Letter 783
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12528
 
10.9%
인 10357
 
9.0%
호 9191
 
8.0%
기 6634
 
5.8%
구 5999
 
5.2%
용 5776
 
5.0%
경 5704
 
5.0%
시 5650
 
4.9%
도 5622
 
4.9%
처 4722
 
4.1%
Other values (160) 43004
37.3%
Decimal Number
ValueCountFrequency (%)
0 33001
35.1%
1 24143
25.7%
2 8618
 
9.2%
3 5162
 
5.5%
4 4788
 
5.1%
6 4424
 
4.7%
5 3754
 
4.0%
7 3529
 
3.8%
9 3289
 
3.5%
8 3281
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 389
49.7%
L 386
49.3%
A 5
 
0.6%
C 2
 
0.3%
D 1
 
0.1%
Space Separator
ValueCountFrequency (%)
57934
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4742
100.0%
Close Punctuation
ValueCountFrequency (%)
] 4381
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 4381
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 165427
58.8%
Hangul 115187
40.9%
Latin 783
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12528
 
10.9%
인 10357
 
9.0%
호 9191
 
8.0%
기 6634
 
5.8%
구 5999
 
5.2%
용 5776
 
5.0%
경 5704
 
5.0%
시 5650
 
4.9%
도 5622
 
4.9%
처 4722
 
4.1%
Other values (160) 43004
37.3%
Common
ValueCountFrequency (%)
57934
35.0%
0 33001
19.9%
1 24143
14.6%
2 8618
 
5.2%
3 5162
 
3.1%
4 4788
 
2.9%
- 4742
 
2.9%
6 4424
 
2.7%
] 4381
 
2.6%
[ 4381
 
2.6%
Other values (4) 13853
 
8.4%
Latin
ValueCountFrequency (%)
B 389
49.7%
L 386
49.3%
A 5
 
0.6%
C 2
 
0.3%
D 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 166210
59.1%
Hangul 115187
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57934
34.9%
0 33001
19.9%
1 24143
14.5%
2 8618
 
5.2%
3 5162
 
3.1%
4 4788
 
2.9%
- 4742
 
2.9%
6 4424
 
2.7%
] 4381
 
2.6%
[ 4381
 
2.6%
Other values (9) 14636
 
8.8%
Hangul
ValueCountFrequency (%)
동 12528
 
10.9%
인 10357
 
9.0%
호 9191
 
8.0%
기 6634
 
5.8%
구 5999
 
5.2%
용 5776
 
5.0%
경 5704
 
5.0%
시 5650
 
4.9%
도 5622
 
4.9%
처 4722
 
4.1%
Other values (160) 43004
37.3%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8268
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95382627
Minimum0
Maximum1.6249651 × 1010
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:35.095361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile749940
Q14896000
median21539660
Q371010785
95-th percentile3.1069926 × 108
Maximum1.6249651 × 1010
Range1.6249651 × 1010
Interquartile range (IQR)66114785

Descriptive statistics

Standard deviation4.328112 × 108
Coefficient of variation (CV)4.5376314
Kurtosis571.72494
Mean95382627
Median Absolute Deviation (MAD)19603660
Skewness20.029468
Sum9.5382627 × 1011
Variance1.8732554 × 1017
MonotonicityNot monotonic
2023-12-13T03:50:35.331768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5882520 44
 
0.4%
39332790 38
 
0.4%
47865900 33
 
0.3%
7393270 33
 
0.3%
41532780 29
 
0.3%
9089280 28
 
0.3%
41064690 27
 
0.3%
34198430 25
 
0.2%
288000 25
 
0.2%
19095100 23
 
0.2%
Other values (8258) 9695
97.0%
ValueCountFrequency (%)
0 1
< 0.1%
12000 1
< 0.1%
19000 1
< 0.1%
24000 1
< 0.1%
24800 1
< 0.1%
28800 1
< 0.1%
33000 1
< 0.1%
36720 1
< 0.1%
50000 1
< 0.1%
54000 1
< 0.1%
ValueCountFrequency (%)
16249651200 1
< 0.1%
15758660320 1
< 0.1%
13905860220 1
< 0.1%
9164402000 1
< 0.1%
8653761090 1
< 0.1%
8421822480 1
< 0.1%
8275109230 1
< 0.1%
8181472560 1
< 0.1%
7057167040 1
< 0.1%
6953555550 1
< 0.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5903
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean233.15966
Minimum0
Maximum28949.5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:50:35.579480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.399
Q130.7425
median83.085
Q3193.5325
95-th percentile766.09011
Maximum28949.5
Range28949.5
Interquartile range (IQR)162.79

Descriptive statistics

Standard deviation816.49569
Coefficient of variation (CV)3.5018737
Kurtosis437.44188
Mean233.15966
Median Absolute Deviation (MAD)64.355
Skewness17.238037
Sum2331596.6
Variance666665.21
MonotonicityNot monotonic
2023-12-13T03:50:35.778912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 411
 
4.1%
27.0 99
 
1.0%
198.0 79
 
0.8%
12.0 58
 
0.6%
10.43 44
 
0.4%
36.0 42
 
0.4%
37.705 40
 
0.4%
13.754 40
 
0.4%
39.69 38
 
0.4%
12.168 38
 
0.4%
Other values (5893) 9111
91.1%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
0.72 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 6
0.1%
1.11 1
 
< 0.1%
1.2 1
 
< 0.1%
1.5231 1
 
< 0.1%
1.65 1
 
< 0.1%
1.67 1
 
< 0.1%
1.68 1
 
< 0.1%
ValueCountFrequency (%)
28949.5 1
< 0.1%
26726.4 1
< 0.1%
23862.48 1
< 0.1%
18853.51 1
< 0.1%
17194.0 1
< 0.1%
14779.62 1
< 0.1%
14349.6844 1
< 0.1%
14096.28 1
< 0.1%
12135.35 1
< 0.1%
11842.59 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021-06-01
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-06-01
2nd row2021-06-01
3rd row2021-06-01
4th row2021-06-01
5th row2021-06-01

Common Values

ValueCountFrequency (%)
2021-06-01 10000
100.0%

Length

2023-12-13T03:50:35.983055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:50:36.117191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-06-01 10000
100.0%

Interactions

2023-12-13T03:50:26.805446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:20.911991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.980510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:23.501450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.575462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:25.706398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:26.980582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.085045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:22.154030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:23.681293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.762793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:25.884627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:27.151493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.267546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:22.780910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:23.851451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.960096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:26.064544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:27.340177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.436249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:22.939325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.031122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:25.119739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:26.220397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:27.507630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.610085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:23.116175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.241170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:25.317411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:26.404254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:27.708787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:21.807709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:23.320955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:24.402485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:25.513146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:50:26.596995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:50:36.212330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명자치단체코드법정동법정리특수지본번부번시가표준액연면적
시군구명1.0001.0000.8240.5090.1850.1610.0220.0470.017
자치단체코드1.0001.0000.8240.5090.1850.1610.0220.0470.017
법정동0.8240.8241.0000.6640.3140.1800.0890.0700.058
법정리0.5090.5090.6641.0000.1550.2300.0850.0520.059
특수지0.1850.1850.3140.1551.0000.2750.0000.1490.077
본번0.1610.1610.1800.2300.2751.0000.0000.0000.000
부번0.0220.0220.0890.0850.0000.0001.0000.0000.000
시가표준액0.0470.0470.0700.0520.1490.0000.0001.0000.913
연면적0.0170.0170.0580.0590.0770.0000.0000.9131.000
2023-12-13T03:50:36.396851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치단체코드시군구명특수지
자치단체코드1.0001.0000.123
시군구명1.0001.0000.123
특수지0.1230.1231.000
2023-12-13T03:50:36.548502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동법정리본번부번시가표준액연면적시군구명자치단체코드특수지
법정동1.0000.7940.150-0.180-0.1490.1570.6180.6180.127
법정리0.7941.0000.032-0.122-0.1640.1230.6180.6180.127
본번0.1500.0321.000-0.1990.0020.0240.1230.1230.168
부번-0.180-0.122-0.1991.0000.027-0.0520.0220.0220.000
시가표준액-0.149-0.1640.0020.0271.0000.7150.0350.0350.067
연면적0.1570.1230.024-0.0520.7151.0000.0170.0170.049
시군구명0.6180.6180.1230.0220.0350.0171.0001.0000.123
자치단체코드0.6180.6180.1230.0220.0350.0171.0001.0000.123
특수지0.1270.1270.1680.0000.0670.0490.1230.1231.000

Missing values

2023-12-13T03:50:27.957983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:50:28.273874image/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

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적데이터기준일자
56032경기도용인시 기흥구41463202111601833012073[ 동백죽전대로 444 ] 0001동 2073호2243592026.522021-06-01
30408경기도용인시 처인구4146120211020126421401[ 낙은로50번길 9-9 ] 0001동 0401호65916240115.442021-06-01
40619경기도용인시 처인구41461202125321151311101[ 백옥대로2402번길 41 ] 0001동 0101호866239038.812021-06-01
36275경기도용인시 처인구41461202110101133371103[ 금령로99번길 15 ] 0001동 0103호1664544054.622021-06-01
28926경기도용인시 처인구4146120211030147000401경기도 용인시 처인구 삼가동 470 401호347227560508.38592021-06-01
14887경기도용인시 처인구41461202125622185210[ 경기동로1085번길 4 ] 0001동 0000호2766400172.92021-06-01
22892경기도용인시 처인구4146120211070162512101[ 금령로140번길 5 ] 0002동 0101호163057000168.12021-06-01
1664경기도용인시 처인구4146120213502311382301101[ 죽양대로 956-38 ] 0001동 0101호89280048.02021-06-01
63271경기도용인시 처인구414612021256271766310경기도 용인시 처인구 이동읍 묵리 766-3 1동2721600388.82021-06-01
59809경기도용인시 처인구41461202125628127711302[ 백옥대로624번길 15 ] 0001동 0302호71746400109.11922021-06-01
시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번동호물건지시가표준액연면적데이터기준일자
53815경기도용인시 기흥구4146320211130144106002101경기도 용인시 기흥구 마북동 441 6002동 101호79555500191.72021-06-01
29901경기도용인시 처인구414612021104023500101경기도 용인시 처인구 남동 산 35 101호4465152073.442021-06-01
26907경기도용인시 처인구4146120211020526711112경기도 용인시 처인구 역북동 0026B0007L 1동 1112호4786590043.9542021-06-01
41383경기도용인시 처인구414612021250271356611215[ 마성로 420 ] 0001동 1215호588252010.432021-06-01
79795경기도용인시 기흥구4146320211020159501106[ 강남로 8 ] 0001동 0106호994710023.352021-06-01
9434경기도용인시 처인구414612021340281245110경기도 용인시 처인구 원삼면 죽능리 245-1 1동7293000143.02021-06-01
26362경기도용인시 처인구414612021105011007201201[ 금어로 2 ] 0001동 0201호2526345054.332021-06-01
25443경기도용인시 처인구41461202110501100700203경기도 용인시 처인구 유방동 1007 203호99144000388.82021-06-01
59490경기도용인시 처인구414612021259311907090001경기도 용인시 처인구 남사읍 완장리 907 9000동 1호54720012.02021-06-01
11397경기도용인시 처인구414612021350241641020경기도 용인시 처인구 백암면 고안리 641 2동1381940197.422021-06-01

Duplicate rows

Most frequently occurring

시도명시군구명자치단체코드과세년도법정동법정리특수지본번부번호물건지시가표준액연면적데이터기준일자# duplicates
0경기도용인시 기흥구4146320211010132621경기도 용인시 기흥구 신갈동 326-2 1동 1호339000030.02021-06-012
1경기도용인시 기흥구41463202110401191141경기도 용인시 기흥구 하갈동 191-14 1동 1호90000018.02021-06-012
2경기도용인시 기흥구41463202110601680101경기도 용인시 기흥구 지곡동 68 1동 101호366410066.622021-06-012
3경기도용인시 기흥구414632021106015031101경기도 용인시 기흥구 지곡동 503-1 1동 101호98865000195.02021-06-012
4경기도용인시 기흥구414632021108015381201경기도 용인시 기흥구 고매동 538-1 1동 201호795744025.922021-06-012
5경기도용인시 기흥구41463202111301731101경기도 용인시 기흥구 마북동 73-1 101호65254500153.542021-06-012
6경기도용인시 처인구414612021104013003101[ 평옥로 17-4 ] 0000동 0101호1575339054.512021-06-012
7경기도용인시 처인구414612021106013412201[ 한터로152번길 28-53 ] 0000동 0201호231008000288.762021-06-012
8경기도용인시 처인구4146120211060154851[ 경안천로258번길 34 ] 0001동 0001호203400018.02021-06-012
9경기도용인시 처인구41461202125027110910경기도 용인시 처인구 포곡읍 전대리 109-1 1동323400077.02021-06-012