Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows314
Duplicate rows (%)3.1%
Total size in memory1.2 MiB
Average record size in memory127.0 B

Variable types

Categorical3
DateTime2
Text2
Numeric7

Dataset

Description가평군 관내 주택외 건물 시가표준액(시군명, 기준년월일, 건물형태, 건물용도, 건물구조, 건물위치, 건물지붕, 물건지지번주소 등) 데이터
Author경기도 가평군
URLhttps://www.data.go.kr/data/15048404/fileData.do

Alerts

시군명 has constant value ""Constant
기준년월일 has constant value ""Constant
Dataset has 314 (3.1%) duplicate rowsDuplicates
건물구조 is highly overall correlated with 시가표준액High correlation
연면적 is highly overall correlated with 전용면적 and 1 other fieldsHigh correlation
전용면적 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
공용면적 is highly overall correlated with 건물형태High correlation
시가표준액 is highly overall correlated with 건물구조 and 2 other fieldsHigh correlation
건물형태 is highly overall correlated with 공용면적High correlation
건물형태 is highly imbalanced (78.4%)Imbalance
공부상 지목 is highly imbalanced (53.6%)Imbalance
연면적 is highly skewed (γ1 = 23.20823632)Skewed
전용면적 is highly skewed (γ1 = 23.20072786)Skewed
시가표준액 is highly skewed (γ1 = 24.26016405)Skewed
공용면적 has 9555 (95.5%) zerosZeros

Reproduction

Analysis started2023-12-12 14:20:37.362380
Analysis finished2023-12-12 14:20:44.965310
Duration7.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 가평군 10000
100.0%

Length

2023-12-12T23:20:45.023355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:45.098345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 10000
50.0%
가평군 10000
50.0%

기준년월일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-09-30 00:00:00
Maximum2021-09-30 00:00:00
2023-12-12T23:20:45.181389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:45.285236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

건물형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9655 
집합
 
345

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row일반
4th row일반
5th row집합

Common Values

ValueCountFrequency (%)
일반 9655
96.5%
집합 345
 
3.5%

Length

2023-12-12T23:20:45.411853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:45.560089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 9655
96.5%
집합 345
 
3.5%
Distinct124
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:20:45.776791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30000
Distinct characters30
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.2%

Sample

1st row391
2nd row362
3rd row302
4th row421
5th row345
ValueCountFrequency (%)
345 1619
16.2%
192 1244
12.4%
362 946
 
9.5%
512 858
 
8.6%
311 679
 
6.8%
714 627
 
6.3%
391 443
 
4.4%
649 382
 
3.8%
41e 287
 
2.9%
189 238
 
2.4%
Other values (114) 2677
26.8%
2023-12-12T23:20:46.187671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7761
25.9%
3 4592
15.3%
2 3924
13.1%
4 3856
12.9%
5 3130
10.4%
9 2804
 
9.3%
6 1505
 
5.0%
7 1079
 
3.6%
8 338
 
1.1%
E 287
 
1.0%
Other values (20) 724
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29110
97.0%
Uppercase Letter 890
 
3.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 287
32.2%
D 183
20.6%
B 164
18.4%
A 115
12.9%
V 35
 
3.9%
H 20
 
2.2%
J 20
 
2.2%
O 13
 
1.5%
L 12
 
1.3%
F 6
 
0.7%
Other values (10) 35
 
3.9%
Decimal Number
ValueCountFrequency (%)
1 7761
26.7%
3 4592
15.8%
2 3924
13.5%
4 3856
13.2%
5 3130
10.8%
9 2804
 
9.6%
6 1505
 
5.2%
7 1079
 
3.7%
8 338
 
1.2%
0 121
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 29110
97.0%
Latin 890
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 287
32.2%
D 183
20.6%
B 164
18.4%
A 115
12.9%
V 35
 
3.9%
H 20
 
2.2%
J 20
 
2.2%
O 13
 
1.5%
L 12
 
1.3%
F 6
 
0.7%
Other values (10) 35
 
3.9%
Common
ValueCountFrequency (%)
1 7761
26.7%
3 4592
15.8%
2 3924
13.5%
4 3856
13.2%
5 3130
10.8%
9 2804
 
9.6%
6 1505
 
5.2%
7 1079
 
3.7%
8 338
 
1.2%
0 121
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7761
25.9%
3 4592
15.3%
2 3924
13.1%
4 3856
12.9%
5 3130
10.4%
9 2804
 
9.3%
6 1505
 
5.0%
7 1079
 
3.6%
8 338
 
1.1%
E 287
 
1.0%
Other values (20) 724
 
2.4%

건물구조
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.3767
Minimum11
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:46.346206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile21
Q121
median25
Q362
95-th percentile62
Maximum99
Range88
Interquartile range (IQR)41

Descriptive statistics

Standard deviation19.609871
Coefficient of variation (CV)0.52465497
Kurtosis-1.2714049
Mean37.3767
Median Absolute Deviation (MAD)4
Skewness0.60768644
Sum373767
Variance384.54705
MonotonicityNot monotonic
2023-12-12T23:20:46.498720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
21 4112
41.1%
62 2103
21.0%
22 695
 
7.0%
61 589
 
5.9%
31 568
 
5.7%
25 517
 
5.2%
51 421
 
4.2%
41 407
 
4.1%
81 217
 
2.2%
74 191
 
1.9%
Other values (18) 180
 
1.8%
ValueCountFrequency (%)
11 65
 
0.7%
12 34
 
0.3%
21 4112
41.1%
22 695
 
7.0%
23 8
 
0.1%
24 1
 
< 0.1%
25 517
 
5.2%
26 8
 
0.1%
27 2
 
< 0.1%
31 568
 
5.7%
ValueCountFrequency (%)
99 1
 
< 0.1%
81 217
2.2%
77 1
 
< 0.1%
75 6
 
0.1%
74 191
1.9%
71 15
 
0.1%
67 8
 
0.1%
65 1
 
< 0.1%
64 1
 
< 0.1%
63 14
 
0.1%

건물위치
Real number (ℝ)

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8292
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:46.699799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q37
95-th percentile11
Maximum15
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.6971383
Coefficient of variation (CV)0.46269441
Kurtosis0.16202839
Mean5.8292
Median Absolute Deviation (MAD)2
Skewness0.81158404
Sum58292
Variance7.2745548
MonotonicityNot monotonic
2023-12-12T23:20:46.857953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
4 2864
28.6%
7 1389
13.9%
5 1334
13.3%
3 839
 
8.4%
8 718
 
7.2%
6 659
 
6.6%
9 561
 
5.6%
11 417
 
4.2%
2 386
 
3.9%
10 240
 
2.4%
Other values (5) 593
 
5.9%
ValueCountFrequency (%)
1 178
 
1.8%
2 386
 
3.9%
3 839
 
8.4%
4 2864
28.6%
5 1334
13.3%
6 659
 
6.6%
7 1389
13.9%
8 718
 
7.2%
9 561
 
5.6%
10 240
 
2.4%
ValueCountFrequency (%)
15 10
 
0.1%
14 41
 
0.4%
13 150
 
1.5%
12 214
 
2.1%
11 417
 
4.2%
10 240
 
2.4%
9 561
5.6%
8 718
7.2%
7 1389
13.9%
6 659
6.6%

건물지붕
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.2039
Minimum11
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:47.029965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q111
median99
Q399
95-th percentile99
Maximum99
Range88
Interquartile range (IQR)88

Descriptive statistics

Standard deviation40.922756
Coefficient of variation (CV)0.64747201
Kurtosis-1.8347022
Mean63.2039
Median Absolute Deviation (MAD)0
Skewness-0.30893074
Sum632039
Variance1674.672
MonotonicityNot monotonic
2023-12-12T23:20:47.143049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
99 5608
56.1%
11 2888
28.9%
31 1187
 
11.9%
22 124
 
1.2%
21 118
 
1.2%
41 74
 
0.7%
42 1
 
< 0.1%
ValueCountFrequency (%)
11 2888
28.9%
21 118
 
1.2%
22 124
 
1.2%
31 1187
 
11.9%
41 74
 
0.7%
42 1
 
< 0.1%
99 5608
56.1%
ValueCountFrequency (%)
99 5608
56.1%
42 1
 
< 0.1%
41 74
 
0.7%
31 1187
 
11.9%
22 124
 
1.2%
21 118
 
1.2%
11 2888
28.9%
Distinct5890
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T23:20:47.552129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length20.7491
Min length16

Characters and Unicode

Total characters207491
Distinct characters119
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

Unique3811 ?
Unique (%)38.1%

Sample

1st row경기도 가평군 조종면 신상리 512-13
2nd row경기도 가평군 설악면 신천리 407-13
3rd row경기도 가평군 상면 연하리 171-1
4th row경기도 가평군 북면 도대리 523-2
5th row경기도 가평군 가평읍 읍내리 637-6 0001동 0205호
ValueCountFrequency (%)
경기도 10000
19.6%
가평군 10000
19.6%
가평읍 2485
 
4.9%
청평면 1868
 
3.7%
설악면 1623
 
3.2%
상면 1587
 
3.1%
조종면 1242
 
2.4%
북면 1195
 
2.3%
읍내리 620
 
1.2%
현리 593
 
1.2%
Other values (4351) 19756
38.8%
2023-12-12T23:20:48.184179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40969
19.7%
14936
 
7.2%
12663
 
6.1%
10173
 
4.9%
10105
 
4.9%
10002
 
4.8%
10002
 
4.8%
10000
 
4.8%
- 7772
 
3.7%
1 7700
 
3.7%
Other values (109) 73169
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117712
56.7%
Decimal Number 41038
 
19.8%
Space Separator 40969
 
19.7%
Dash Punctuation 7772
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14936
12.7%
12663
10.8%
10173
 
8.6%
10105
 
8.6%
10002
 
8.5%
10002
 
8.5%
10000
 
8.5%
7515
 
6.4%
3105
 
2.6%
2449
 
2.1%
Other values (97) 26762
22.7%
Decimal Number
ValueCountFrequency (%)
1 7700
18.8%
2 5382
13.1%
4 4654
11.3%
3 4584
11.2%
0 4001
9.7%
5 3724
9.1%
6 3374
8.2%
7 2934
 
7.1%
9 2505
 
6.1%
8 2180
 
5.3%
Space Separator
ValueCountFrequency (%)
40969
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7772
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117712
56.7%
Common 89779
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14936
12.7%
12663
10.8%
10173
 
8.6%
10105
 
8.6%
10002
 
8.5%
10002
 
8.5%
10000
 
8.5%
7515
 
6.4%
3105
 
2.6%
2449
 
2.1%
Other values (97) 26762
22.7%
Common
ValueCountFrequency (%)
40969
45.6%
- 7772
 
8.7%
1 7700
 
8.6%
2 5382
 
6.0%
4 4654
 
5.2%
3 4584
 
5.1%
0 4001
 
4.5%
5 3724
 
4.1%
6 3374
 
3.8%
7 2934
 
3.3%
Other values (2) 4685
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117712
56.7%
ASCII 89779
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40969
45.6%
- 7772
 
8.7%
1 7700
 
8.6%
2 5382
 
6.0%
4 4654
 
5.2%
3 4584
 
5.1%
0 4001
 
4.5%
5 3724
 
4.1%
6 3374
 
3.8%
7 2934
 
3.3%
Other values (2) 4685
 
5.2%
Hangul
ValueCountFrequency (%)
14936
12.7%
12663
10.8%
10173
 
8.6%
10105
 
8.6%
10002
 
8.5%
10002
 
8.5%
10000
 
8.5%
7515
 
6.4%
3105
 
2.6%
2449
 
2.1%
Other values (97) 26762
22.7%

연면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5725
Distinct (%)57.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.94845
Minimum0
Maximum20563.06
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:48.368666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.519
Q140.2475
median82.515
Q3150.3025
95-th percentile498.036
Maximum20563.06
Range20563.06
Interquartile range (IQR)110.055

Descriptive statistics

Standard deviation414.4587
Coefficient of variation (CV)2.6075039
Kurtosis916.31081
Mean158.94845
Median Absolute Deviation (MAD)48.375
Skewness23.208236
Sum1589484.5
Variance171776.01
MonotonicityNot monotonic
2023-12-12T23:20:48.539207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 197
 
2.0%
66.0 77
 
0.8%
99.0 48
 
0.5%
36.0 45
 
0.4%
60.0 40
 
0.4%
95.498 39
 
0.4%
82.2 39
 
0.4%
198.0 38
 
0.4%
72.0 36
 
0.4%
24.0 34
 
0.3%
Other values (5715) 9407
94.1%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
0.49 1
 
< 0.1%
0.81 1
 
< 0.1%
0.93 2
< 0.1%
1.0 3
< 0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
1.7 1
 
< 0.1%
1.71 1
 
< 0.1%
1.86 1
 
< 0.1%
ValueCountFrequency (%)
20563.06 1
< 0.1%
17030.25 1
< 0.1%
7946.0 1
< 0.1%
7663.0 1
< 0.1%
7569.74 1
< 0.1%
6113.48 1
< 0.1%
5247.35 1
< 0.1%
5095.86 1
< 0.1%
5076.49 1
< 0.1%
4998.71 1
< 0.1%

전용면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5694
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.483
Minimum0
Maximum20563.06
Zeros30
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:48.715276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.8695
Q139.645
median79.92
Q3149.76
95-th percentile497.753
Maximum20563.06
Range20563.06
Interquartile range (IQR)110.115

Descriptive statistics

Standard deviation414.55836
Coefficient of variation (CV)2.6324007
Kurtosis915.75353
Mean157.483
Median Absolute Deviation (MAD)47.705
Skewness23.200728
Sum1574830
Variance171858.63
MonotonicityNot monotonic
2023-12-12T23:20:48.894445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.0 197
 
2.0%
66.0 77
 
0.8%
40.5 63
 
0.6%
99.0 47
 
0.5%
36.0 45
 
0.4%
60.0 40
 
0.4%
72.415 39
 
0.4%
198.0 38
 
0.4%
45.0 37
 
0.4%
26.1 37
 
0.4%
Other values (5684) 9380
93.8%
ValueCountFrequency (%)
0.0 30
0.3%
0.49 1
 
< 0.1%
0.81 1
 
< 0.1%
0.93 2
 
< 0.1%
1.0 3
 
< 0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
1.7 1
 
< 0.1%
1.71 1
 
< 0.1%
1.86 1
 
< 0.1%
ValueCountFrequency (%)
20563.06 1
< 0.1%
17030.25 1
< 0.1%
7946.0 1
< 0.1%
7663.0 1
< 0.1%
7569.74 1
< 0.1%
6113.48 1
< 0.1%
5247.35 1
< 0.1%
5095.86 1
< 0.1%
5076.49 1
< 0.1%
4998.71 1
< 0.1%

공용면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct153
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4654487
Minimum0
Maximum241.51
Zeros9555
Zeros (%)95.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:49.072331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum241.51
Range241.51
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.9711177
Coefficient of variation (CV)6.8041395
Kurtosis158.95602
Mean1.4654487
Median Absolute Deviation (MAD)0
Skewness11.050209
Sum14654.487
Variance99.423187
MonotonicityNot monotonic
2023-12-12T23:20:49.238287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9555
95.5%
41.7 39
 
0.4%
23.083 39
 
0.4%
46.33 22
 
0.2%
22.54 18
 
0.2%
99.63 18
 
0.2%
8.11 17
 
0.2%
24.9 14
 
0.1%
10.21 13
 
0.1%
9.35 13
 
0.1%
Other values (143) 252
 
2.5%
ValueCountFrequency (%)
0.0 9555
95.5%
0.129 1
 
< 0.1%
0.1298 3
 
< 0.1%
0.13 1
 
< 0.1%
0.1353 1
 
< 0.1%
0.18 1
 
< 0.1%
0.19 1
 
< 0.1%
1.43 1
 
< 0.1%
2.94 1
 
< 0.1%
3.02 1
 
< 0.1%
ValueCountFrequency (%)
241.51 1
< 0.1%
204.34 1
< 0.1%
197.82 1
< 0.1%
185.18 1
< 0.1%
165.75 1
< 0.1%
163.83 1
< 0.1%
162.0 1
< 0.1%
160.63 1
< 0.1%
157.81 1
< 0.1%
154.85 1
< 0.1%
Distinct1868
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2017-06-01 00:00:00
2023-12-12T23:20:49.393867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:49.573955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

공부상 지목
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
08 대지
6585 
28 잡종지
670 
01 전
 
576
02 답
 
383
05 임야
 
343
Other values (18)
1443 

Length

Max length8
Median length5
Mean length5.2483
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row08 대지
2nd row08 대지
3rd row08 대지
4th row01 전
5th row08 대지

Common Values

ValueCountFrequency (%)
08 대지 6585
65.8%
28 잡종지 670
 
6.7%
01 전 576
 
5.8%
02 답 383
 
3.8%
05 임야 343
 
3.4%
25 종교용지 271
 
2.7%
04 목장용지 266
 
2.7%
09 공장용지 215
 
2.1%
10 학교용지 213
 
2.1%
13 창고용지 213
 
2.1%
Other values (13) 265
 
2.6%

Length

2023-12-12T23:20:49.770735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
08 6585
32.9%
대지 6585
32.9%
28 670
 
3.4%
잡종지 670
 
3.4%
01 576
 
2.9%
576
 
2.9%
02 383
 
1.9%
383
 
1.9%
05 343
 
1.7%
임야 343
 
1.7%
Other values (36) 2886
14.4%

시가표준액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8624
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59229626
Minimum0
Maximum9.5433161 × 109
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:49.980785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile854985
Q15691750
median21547980
Q355674615
95-th percentile1.962984 × 108
Maximum9.5433161 × 109
Range9.5433161 × 109
Interquartile range (IQR)49982865

Descriptive statistics

Standard deviation2.0648391 × 108
Coefficient of variation (CV)3.4861592
Kurtosis915.93335
Mean59229626
Median Absolute Deviation (MAD)18650400
Skewness24.260164
Sum5.9229626 × 1011
Variance4.2635605 × 1016
MonotonicityNot monotonic
2023-12-12T23:20:50.155208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34195200 39
 
0.4%
54051868 39
 
0.4%
37993280 22
 
0.2%
2376000 19
 
0.2%
53632462 18
 
0.2%
38375550 17
 
0.2%
14849010 17
 
0.2%
196298400 16
 
0.2%
2322000 15
 
0.1%
660000 14
 
0.1%
Other values (8614) 9784
97.8%
ValueCountFrequency (%)
0 1
< 0.1%
39600 1
< 0.1%
43323 1
< 0.1%
43700 1
< 0.1%
50890 1
< 0.1%
57000 1
< 0.1%
60000 1
< 0.1%
63840 1
< 0.1%
67200 1
< 0.1%
72000 1
< 0.1%
ValueCountFrequency (%)
9543316146 1
< 0.1%
9032844600 1
< 0.1%
5456056000 1
< 0.1%
5389654880 1
< 0.1%
2837266068 1
< 0.1%
2582450000 1
< 0.1%
2526908098 1
< 0.1%
2515350872 1
< 0.1%
2383915200 1
< 0.1%
2297525440 1
< 0.1%

Interactions

2023-12-12T23:20:43.938490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.185607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.805508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.598029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.386142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.222454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.180942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.033761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.270822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.903272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.708995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.502538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.330433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.268217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.126921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.358441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.012506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.831079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.627185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.422094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.382641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.239048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.452481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.137478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.943666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.739166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.507962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.492368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.353681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.542570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.252986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.032472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.839524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.603470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.600599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.450093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.623459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.360078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.136814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.953804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.692356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.719977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:44.568031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:39.705516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:40.463152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:41.262157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.092792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:42.776501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:43.845950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:20:50.270796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물형태건물구조건물위치건물지붕연면적전용면적공용면적공부상 지목시가표준액
건물형태1.0000.1540.3120.0950.0000.0000.7690.1100.000
건물구조0.1541.0000.2520.4900.0420.0420.0720.3880.099
건물위치0.3120.2521.0000.4110.0520.0520.2520.5730.064
건물지붕0.0950.4900.4111.0000.0000.0000.1840.2720.018
연면적0.0000.0420.0520.0001.0001.0000.0000.2860.875
전용면적0.0000.0420.0520.0001.0001.0000.0000.2860.875
공용면적0.7690.0720.2520.1840.0000.0001.0000.1810.000
공부상 지목0.1100.3880.5730.2720.2860.2860.1811.0000.301
시가표준액0.0000.0990.0640.0180.8750.8750.0000.3011.000
2023-12-12T23:20:50.717979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공부상 지목건물형태
공부상 지목1.0000.096
건물형태0.0961.000
2023-12-12T23:20:50.816733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물구조건물위치건물지붕연면적전용면적공용면적시가표준액건물형태공부상 지목
건물구조1.000-0.2790.195-0.281-0.260-0.179-0.6780.1530.160
건물위치-0.2791.000-0.2680.0270.0150.0940.1990.1940.252
건물지붕0.195-0.2681.000-0.113-0.101-0.0450.0360.1160.137
연면적-0.2810.027-0.1131.0000.990-0.0180.6910.0000.133
전용면적-0.2600.015-0.1010.9901.000-0.1200.6750.0000.133
공용면적-0.1790.094-0.045-0.018-0.1201.0000.0940.6060.068
시가표준액-0.6780.1990.0360.6910.6750.0941.0000.0000.153
건물형태0.1530.1940.1160.0000.0000.6060.0001.0000.096
공부상 지목0.1600.2520.1370.1330.1330.0680.1530.0961.000

Missing values

2023-12-12T23:20:44.697357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:20:44.863934image/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

시군명기준년월일건물형태건물용도건물구조건물위치건물지붕물건지 지번주소연면적전용면적공용면적준공일자공부상 지목시가표준액
18158경기도 가평군2021-09-30일반39121499경기도 가평군 조종면 신상리 512-1324.324.30.02013-06-2008 대지16086600
6553경기도 가평군2021-09-30일반362211199경기도 가평군 설악면 신천리 407-13307.36307.360.02012-03-2708 대지173351040
16551경기도 가평군2021-09-30일반30221611경기도 가평군 상면 연하리 171-1149.29149.290.01997-01-0108 대지69464637
20121경기도 가평군2021-09-30일반42151331경기도 가평군 북면 도대리 523-241.341.30.01980-01-0101 전2023700
1769경기도 가평군2021-09-30집합34521911경기도 가평군 가평읍 읍내리 637-6 0001동 0205호83.063.0319.971997-01-0108 대지37433000
21376경기도 가평군2021-09-30일반19D62499경기도 가평군 북면 제령리 556-425.025.00.02013-07-1708 대지7775000
3861경기도 가평군2021-09-30집합39121799경기도 가평군 가평읍 금대리 49-11 0001동 0102호35.8326.19.732004-01-0108 대지22465410
10359경기도 가평군2021-09-30일반19221799경기도 가평군 청평면 고성리 764-5176.67176.670.02012-11-1508 대지97875180
15077경기도 가평군2021-09-30일반19222499경기도 가평군 상면 임초리 64-35.05.00.02004-01-0108 대지1755000
19421경기도 가평군2021-09-30일반34531411경기도 가평군 조종면 운악리 198-121.4221.420.01991-01-0101 전3170160
시군명기준년월일건물형태건물용도건물구조건물위치건물지붕물건지 지번주소연면적전용면적공용면적준공일자공부상 지목시가표준액
3142경기도 가평군2021-09-30일반19221599경기도 가평군 가평읍 하색리 778-1096.5896.580.02012-08-1008 대지51187400
21871경기도 가평군2021-09-30일반71462431경기도 가평군 북면 적목리 12722.022.00.01998-01-0108 대지330000
9451경기도 가평군2021-09-30일반19221799경기도 가평군 청평면 대성리 412-1152.68152.680.02010-09-1608 대지80920400
18878경기도 가평군2021-09-30일반39121499경기도 가평군 조종면 운악리 417-1035.8135.810.02011-09-1508 대지22667730
6934경기도 가평군2021-09-30일반42951411경기도 가평군 설악면 묵안리 328105.0105.00.01994-01-0125 종교용지16380000
20995경기도 가평군2021-09-30일반71462399경기도 가평군 북면 목동리 10382.6282.620.02002-01-0101 전2643840
20202경기도 가평군2021-09-30일반34521811경기도 가평군 북면 목동리 886-18181.71181.710.01995-01-0108 대지74864520
15627경기도 가평군2021-09-30일반36262731경기도 가평군 상면 덕현리 6-20157.15157.150.02001-01-0108 대지19015150
19561경기도 가평군2021-09-30일반64921599경기도 가평군 조종면 현리 41-297.4497.440.02016-01-0808 대지33714240
5043경기도 가평군2021-09-30일반345411211경기도 가평군 가평읍 읍내리 495-25107.1107.10.01973-01-0108 대지7711200

Duplicate rows

Most frequently occurring

시군명기준년월일건물형태건물용도건물구조건물위치건물지붕물건지 지번주소연면적전용면적공용면적준공일자공부상 지목시가표준액# duplicates
13경기도 가평군2021-09-30일반18921599경기도 가평군 조종면 현리 477-30995.49872.41523.0832015-10-2428 잡종지5405186839
12경기도 가평군2021-09-30일반18921599경기도 가평군 조종면 현리 477-30994.75772.21722.542015-10-2428 잡종지5363246218
4경기도 가평군2021-09-30일반18921411경기도 가평군 조종면 운악리 51437.8537.850.02000-01-0101 전1438300011
5경기도 가평군2021-09-30일반18921411경기도 가평군 조종면 운악리 51439.3439.340.02000-01-0101 전149492009
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