Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory498.0 KiB
Average record size in memory51.0 B

Variable types

Text1
Categorical1
Numeric3

Dataset

Description국토교통부장관이 매년 공시하는 표준지 공시지가를 기준으로 하동군수가 조사한 개별토지의 특성과 비교표준지의 특성을 비교하여, 국토교통부장관이 개발 공급한 토지가격비준표상의 토지특성차이에 따른 가격배율을 산출하고, 이를 표준지 공시지가에 곱하여 산정한 후 감정평가업자의 검증을 받아 토지소유자 등의 의견 수렴과 하동군부동산평가위원회 심의 등의 절차를 거쳐 하동군수가 결정ㆍ공시하는 개별토지의 단위면적당 가격(원/㎡).
URLhttps://www.data.go.kr/data/15002805/fileData.do

Alerts

전년지가 is highly overall correlated with 결정지가High correlation
결정지가 is highly overall correlated with 전년지가High correlation
면적 is highly skewed (γ1 = 99.47505329)Skewed
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:08:46.695310
Analysis finished2023-12-12 15:08:48.617645
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소재지
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T00:08:48.902021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.4446
Min length12

Characters and Unicode

Total characters164446
Distinct characters73
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row하동군 화개면 덕은리 452-2
2nd row하동군 악양면 매계리 125-4
3rd row하동군 화개면 덕은리 117
4th row하동군 악양면 신흥리 산 14-8
5th row하동군 적량면 우계리 1205
ValueCountFrequency (%)
하동군 10000
24.4%
악양면 3204
 
7.8%
하동읍 2534
 
6.2%
화개면 2453
 
6.0%
적량면 1809
 
4.4%
산 1067
 
2.6%
우계리 481
 
1.2%
읍내리 448
 
1.1%
화심리 428
 
1.0%
동산리 411
 
1.0%
Other values (6219) 18232
44.4%
2023-12-13T00:08:49.401199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31067
18.9%
동 13593
 
8.3%
하 12534
 
7.6%
리 10000
 
6.1%
군 10000
 
6.1%
1 7648
 
4.7%
면 7466
 
4.5%
- 6187
 
3.8%
2 4745
 
2.9%
3 4080
 
2.5%
Other values (63) 57126
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89908
54.7%
Decimal Number 37284
22.7%
Space Separator 31067
 
18.9%
Dash Punctuation 6187
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 13593
15.1%
하 12534
13.9%
리 10000
11.1%
군 10000
11.1%
면 7466
 
8.3%
양 3204
 
3.6%
악 3204
 
3.6%
읍 2982
 
3.3%
화 2881
 
3.2%
개 2453
 
2.7%
Other values (51) 21591
24.0%
Decimal Number
ValueCountFrequency (%)
1 7648
20.5%
2 4745
12.7%
3 4080
10.9%
4 3497
9.4%
5 3261
8.7%
6 3073
8.2%
7 3033
 
8.1%
8 2808
 
7.5%
9 2663
 
7.1%
0 2476
 
6.6%
Space Separator
ValueCountFrequency (%)
31067
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6187
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89908
54.7%
Common 74538
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 13593
15.1%
하 12534
13.9%
리 10000
11.1%
군 10000
11.1%
면 7466
 
8.3%
양 3204
 
3.6%
악 3204
 
3.6%
읍 2982
 
3.3%
화 2881
 
3.2%
개 2453
 
2.7%
Other values (51) 21591
24.0%
Common
ValueCountFrequency (%)
31067
41.7%
1 7648
 
10.3%
- 6187
 
8.3%
2 4745
 
6.4%
3 4080
 
5.5%
4 3497
 
4.7%
5 3261
 
4.4%
6 3073
 
4.1%
7 3033
 
4.1%
8 2808
 
3.8%
Other values (2) 5139
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89908
54.7%
ASCII 74538
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31067
41.7%
1 7648
 
10.3%
- 6187
 
8.3%
2 4745
 
6.4%
3 4080
 
5.5%
4 3497
 
4.7%
5 3261
 
4.4%
6 3073
 
4.1%
7 3033
 
4.1%
8 2808
 
3.8%
Other values (2) 5139
 
6.9%
Hangul
ValueCountFrequency (%)
동 13593
15.1%
하 12534
13.9%
리 10000
11.1%
군 10000
11.1%
면 7466
 
8.3%
양 3204
 
3.6%
악 3204
 
3.6%
읍 2982
 
3.3%
화 2881
 
3.2%
개 2453
 
2.7%
Other values (51) 21591
24.0%

지목
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
답
2457 
임
2017 
도
1844 
전
1531 
대
1193 
Other values (18)
958 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row답
2nd row도
3rd row임
4th row임
5th row임

Common Values

ValueCountFrequency (%)
답 2457
24.6%
임 2017
20.2%
도 1844
18.4%
전 1531
15.3%
대 1193
11.9%
구 354
 
3.5%
천 104
 
1.0%
묘 103
 
1.0%
제 89
 
0.9%
창 64
 
0.6%
Other values (13) 244
 
2.4%

Length

2023-12-13T00:08:49.535144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
답 2457
24.6%
임 2017
20.2%
도 1844
18.4%
전 1531
15.3%
대 1193
11.9%
구 354
 
3.5%
천 104
 
1.0%
묘 103
 
1.0%
제 89
 
0.9%
창 64
 
0.6%
Other values (13) 244
 
2.4%

면적
Real number (ℝ)

SKEWED 

Distinct2534
Distinct (%)25.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7500.5557
Minimum1
Maximum53723252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:08:49.685075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q196
median316.5
Q3933
95-th percentile4764.3
Maximum53723252
Range53723251
Interquartile range (IQR)837

Descriptive statistics

Standard deviation538180.52
Coefficient of variation (CV)71.752086
Kurtosis9928.1935
Mean7500.5557
Median Absolute Deviation (MAD)266.5
Skewness99.475053
Sum75005557
Variance2.8963827 × 1011
MonotonicityNot monotonic
2023-12-13T00:08:49.853983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 84
 
0.8%
10.0 67
 
0.7%
13.0 60
 
0.6%
3.0 59
 
0.6%
99.0 58
 
0.6%
66.0 57
 
0.6%
26.0 56
 
0.6%
23.0 54
 
0.5%
17.0 54
 
0.5%
50.0 53
 
0.5%
Other values (2524) 9398
94.0%
ValueCountFrequency (%)
1.0 14
 
0.1%
2.0 24
 
0.2%
3.0 59
0.6%
4.0 21
 
0.2%
4.5 1
 
< 0.1%
5.0 43
0.4%
6.0 33
 
0.3%
7.0 84
0.8%
7.9 1
 
< 0.1%
8.0 33
 
0.3%
ValueCountFrequency (%)
53723252.0 1
< 0.1%
2517500.0 1
< 0.1%
1880007.0 1
< 0.1%
264099.0 1
< 0.1%
165322.0 1
< 0.1%
154810.0 1
< 0.1%
134876.0 1
< 0.1%
131901.0 1
< 0.1%
129322.0 1
< 0.1%
126744.0 1
< 0.1%

전년지가
Real number (ℝ)

HIGH CORRELATION 

Distinct2271
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36728.999
Minimum0
Maximum1534000
Zeros16
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:08:49.987477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile520
Q13200
median10500
Q327000
95-th percentile146920
Maximum1534000
Range1534000
Interquartile range (IQR)23800

Descriptive statistics

Standard deviation104158.81
Coefficient of variation (CV)2.8358739
Kurtosis72.202169
Mean36728.999
Median Absolute Deviation (MAD)8950
Skewness7.5451594
Sum3.6728999 × 108
Variance1.0849057 × 1010
MonotonicityNot monotonic
2023-12-13T00:08:50.108921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4290 94
 
0.9%
5940 72
 
0.7%
13000 65
 
0.7%
5110 63
 
0.6%
6760 58
 
0.6%
6270 55
 
0.5%
4450 54
 
0.5%
4120 50
 
0.5%
13200 50
 
0.5%
10500 47
 
0.5%
Other values (2261) 9392
93.9%
ValueCountFrequency (%)
0 16
0.2%
108 2
 
< 0.1%
110 4
 
< 0.1%
113 3
 
< 0.1%
118 9
0.1%
127 11
0.1%
128 1
 
< 0.1%
136 1
 
< 0.1%
143 1
 
< 0.1%
153 5
 
0.1%
ValueCountFrequency (%)
1534000 1
< 0.1%
1512000 1
< 0.1%
1489000 1
< 0.1%
1435000 2
< 0.1%
1391000 1
< 0.1%
1367000 1
< 0.1%
1342000 2
< 0.1%
1339000 1
< 0.1%
1291000 1
< 0.1%
1241000 1
< 0.1%

결정지가
Real number (ℝ)

HIGH CORRELATION 

Distinct2316
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34415.878
Minimum100
Maximum1487000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:08:50.257303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile493
Q12990
median9800
Q325100
95-th percentile139600
Maximum1487000
Range1486900
Interquartile range (IQR)22110

Descriptive statistics

Standard deviation99251.746
Coefficient of variation (CV)2.883894
Kurtosis74.689958
Mean34415.878
Median Absolute Deviation (MAD)8290
Skewness7.6748832
Sum3.4415878 × 108
Variance9.8509091 × 109
MonotonicityNot monotonic
2023-12-13T00:08:50.415382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3960 78
 
0.8%
12000 56
 
0.6%
12200 55
 
0.5%
4120 48
 
0.5%
6270 42
 
0.4%
16600 42
 
0.4%
10400 41
 
0.4%
5640 38
 
0.4%
4710 38
 
0.4%
12500 37
 
0.4%
Other values (2306) 9525
95.2%
ValueCountFrequency (%)
100 2
 
< 0.1%
101 4
 
< 0.1%
104 3
 
< 0.1%
109 9
0.1%
117 11
0.1%
118 1
 
< 0.1%
126 1
 
< 0.1%
132 1
 
< 0.1%
141 5
0.1%
147 1
 
< 0.1%
ValueCountFrequency (%)
1487000 1
 
< 0.1%
1457000 1
 
< 0.1%
1403000 1
 
< 0.1%
1334000 1
 
< 0.1%
1332000 3
< 0.1%
1296000 1
 
< 0.1%
1287000 1
 
< 0.1%
1265000 1
 
< 0.1%
1246000 2
< 0.1%
1225000 1
 
< 0.1%

Interactions

2023-12-13T00:08:48.166924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:47.397737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:47.807702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:48.265940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:47.514973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:47.917257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:48.367307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:47.666843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:08:48.038479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:08:50.508420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지목면적전년지가결정지가
지목1.0000.0000.3650.365
면적0.0001.0000.0000.000
전년지가0.3650.0001.0000.977
결정지가0.3650.0000.9771.000
2023-12-13T00:08:50.620244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적전년지가결정지가지목
면적1.000-0.124-0.1250.000
전년지가-0.1241.0000.9940.143
결정지가-0.1250.9941.0000.143
지목0.0000.1430.1431.000

Missing values

2023-12-13T00:08:48.485211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:08:48.575604image/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

소재지지목면적전년지가결정지가
27719하동군 화개면 덕은리 452-2답782.01300012000
64944하동군 악양면 매계리 125-4도501.034603210
27138하동군 화개면 덕은리 117임142.0486449
57873하동군 악양면 신흥리 산 14-8임347.0688636
82574하동군 적량면 우계리 1205임238.022702110
19076하동군 하동읍 화심리 1058-14임304.041303860
22028하동군 하동읍 두곡리 735-6도76.090708410
14897하동군 하동읍 흥룡리 1099-4답2460.05850052200
32695하동군 화개면 삼신리 383전473.070006460
41758하동군 화개면 범왕리 291임1405.0490411
소재지지목면적전년지가결정지가
2330하동군 하동읍 읍내리 572-4대329.09730089400
38704하동군 화개면 용강리 63대469.04930045800
38172하동군 화개면 운수리 757전1686.0106009820
38874하동군 화개면 용강리 141-3대455.0136200126400
73777하동군 악양면 봉대리 224전347.01200011000
81518하동군 적량면 우계리 603대3031.04050037500
883하동군 하동읍 읍내리 237-34구45.0323000297000
42591하동군 화개면 범왕리 962임1045.0375347
8812하동군 하동읍 신기리 39-1전347.083007720
19432하동군 하동읍 화심리 1307임89.0793732