Overview

Dataset statistics

Number of variables5
Number of observations147
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory43.9 B

Variable types

Numeric3
Categorical1
Text1

Dataset

Description공공용지 이의재결취득현황을 아래와 같이 제공합니다. 제공정보 - 사업종류,사업명,토지_면적(제곱미터),토지_보상금액(원)
URLhttps://www.data.go.kr/data/15049041/fileData.do

Alerts

토지_면적(제곱미터) is highly overall correlated with 토지_보상금액(원)High correlation
토지_보상금액(원) is highly overall correlated with 토지_면적(제곱미터)High correlation
순번 has unique valuesUnique
토지_보상금액(원) has 2 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-12 23:49:02.329388
Analysis finished2023-12-12 23:49:03.649778
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct147
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T08:49:03.724889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.3
Q137.5
median74
Q3110.5
95-th percentile139.7
Maximum147
Range146
Interquartile range (IQR)73

Descriptive statistics

Standard deviation42.579338
Coefficient of variation (CV)0.57539646
Kurtosis-1.2
Mean74
Median Absolute Deviation (MAD)37
Skewness0
Sum10878
Variance1813
MonotonicityStrictly increasing
2023-12-13T08:49:04.086071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
Other values (137) 137
93.2%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%

사업종류
Categorical

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
수도
70 
댐
51 
단지
25 
기타
 
1

Length

Max length2
Median length2
Mean length1.6530612
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row댐
2nd row기타
3rd row수도
4th row댐
5th row댐

Common Values

ValueCountFrequency (%)
수도 70
47.6%
댐 51
34.7%
단지 25
 
17.0%
기타 1
 
0.7%

Length

2023-12-13T08:49:04.227105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:49:04.319707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수도 70
47.6%
댐 51
34.7%
단지 25
 
17.0%
기타 1
 
0.7%

사업명
Text

Distinct146
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T08:49:04.500490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length16.591837
Min length4

Characters and Unicode

Total characters2439
Distinct characters223
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)98.6%

Sample

1st row부항다목적댐건설사업
2nd row이관사업
3rd row금강북부급수체계조정(청양계통)
4th row용담댐 직하류 하천정비공사
5th row충주댐 치수능력증대사업
ValueCountFrequency (%)
건설사업 14
 
3.9%
직하류 12
 
3.4%
시화mtv 6
 
1.7%
설치사업 6
 
1.7%
하천정비공사 6
 
1.7%
하천정비사업 5
 
1.4%
용수공급사업 5
 
1.4%
시화2단계(송산그린시티 5
 
1.4%
급수체계조정사업 5
 
1.4%
시화 4
 
1.1%
Other values (231) 288
80.9%
2023-12-13T08:49:04.835021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
 
8.6%
업 149
 
6.1%
사 141
 
5.8%
수 93
 
3.8%
) 57
 
2.3%
( 57
 
2.3%
설 54
 
2.2%
도 51
 
2.1%
하 50
 
2.1%
계 50
 
2.1%
Other values (213) 1528
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2005
82.2%
Space Separator 209
 
8.6%
Close Punctuation 58
 
2.4%
Open Punctuation 58
 
2.4%
Uppercase Letter 53
 
2.2%
Decimal Number 46
 
1.9%
Connector Punctuation 5
 
0.2%
Letter Number 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 149
 
7.4%
사 141
 
7.0%
수 93
 
4.6%
설 54
 
2.7%
도 51
 
2.5%
하 50
 
2.5%
계 50
 
2.5%
시 48
 
2.4%
댐 46
 
2.3%
공 44
 
2.2%
Other values (187) 1279
63.8%
Uppercase Letter
ValueCountFrequency (%)
T 13
24.5%
V 12
22.6%
M 12
22.6%
I 5
 
9.4%
K 2
 
3.8%
C 2
 
3.8%
G 2
 
3.8%
P 2
 
3.8%
S 2
 
3.8%
R 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
2 21
45.7%
1 13
28.3%
3 3
 
6.5%
4 3
 
6.5%
0 2
 
4.3%
7 2
 
4.3%
5 1
 
2.2%
6 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 57
98.3%
] 1
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 57
98.3%
[ 1
 
1.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅲ 2
40.0%
Space Separator
ValueCountFrequency (%)
209
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2005
82.2%
Common 376
 
15.4%
Latin 58
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 149
 
7.4%
사 141
 
7.0%
수 93
 
4.6%
설 54
 
2.7%
도 51
 
2.5%
하 50
 
2.5%
계 50
 
2.5%
시 48
 
2.4%
댐 46
 
2.3%
공 44
 
2.2%
Other values (187) 1279
63.8%
Common
ValueCountFrequency (%)
209
55.6%
) 57
 
15.2%
( 57
 
15.2%
2 21
 
5.6%
1 13
 
3.5%
_ 5
 
1.3%
3 3
 
0.8%
4 3
 
0.8%
0 2
 
0.5%
7 2
 
0.5%
Other values (4) 4
 
1.1%
Latin
ValueCountFrequency (%)
T 13
22.4%
V 12
20.7%
M 12
20.7%
I 5
 
8.6%
Ⅱ 3
 
5.2%
K 2
 
3.4%
C 2
 
3.4%
G 2
 
3.4%
P 2
 
3.4%
Ⅲ 2
 
3.4%
Other values (2) 3
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2005
82.2%
ASCII 429
 
17.6%
Number Forms 5
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
48.7%
) 57
 
13.3%
( 57
 
13.3%
2 21
 
4.9%
1 13
 
3.0%
T 13
 
3.0%
V 12
 
2.8%
M 12
 
2.8%
I 5
 
1.2%
_ 5
 
1.2%
Other values (14) 25
 
5.8%
Hangul
ValueCountFrequency (%)
업 149
 
7.4%
사 141
 
7.0%
수 93
 
4.6%
설 54
 
2.7%
도 51
 
2.5%
하 50
 
2.5%
계 50
 
2.5%
시 48
 
2.4%
댐 46
 
2.3%
공 44
 
2.2%
Other values (187) 1279
63.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
60.0%
Ⅲ 2
40.0%

토지_면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct146
Distinct (%)100.0%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean611631.5
Minimum23
Maximum17350799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T08:49:04.994676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile346.25
Q14329.25
median38387.5
Q3143984
95-th percentile2832462.2
Maximum17350799
Range17350776
Interquartile range (IQR)139654.75

Descriptive statistics

Standard deviation2300037.9
Coefficient of variation (CV)3.7604961
Kurtosis33.108224
Mean611631.5
Median Absolute Deviation (MAD)37376
Skewness5.5373689
Sum89298199
Variance5.2901741 × 1012
MonotonicityNot monotonic
2023-12-13T08:49:05.135162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4409130 1
 
0.7%
48 1
 
0.7%
452436 1
 
0.7%
30281 1
 
0.7%
5387 1
 
0.7%
436 1
 
0.7%
1276 1
 
0.7%
2879182 1
 
0.7%
2692303 1
 
0.7%
84445 1
 
0.7%
Other values (136) 136
92.5%
ValueCountFrequency (%)
23 1
0.7%
48 1
0.7%
71 1
0.7%
111 1
0.7%
186 1
0.7%
190 1
0.7%
216 1
0.7%
344 1
0.7%
353 1
0.7%
436 1
0.7%
ValueCountFrequency (%)
17350799 1
0.7%
15343949 1
0.7%
10677801 1
0.7%
8331748 1
0.7%
6297409 1
0.7%
4409130 1
0.7%
3541787 1
0.7%
2879182 1
0.7%
2692303 1
0.7%
2173819 1
0.7%

토지_보상금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct145
Distinct (%)99.3%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean2.8614361 × 1010
Minimum0
Maximum1.60811 × 1012
Zeros2
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T08:49:05.261845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6757090
Q197691900
median1.0563083 × 109
Q34.4153326 × 109
95-th percentile7.1012362 × 1010
Maximum1.60811 × 1012
Range1.60811 × 1012
Interquartile range (IQR)4.3176407 × 109

Descriptive statistics

Standard deviation1.4869551 × 1011
Coefficient of variation (CV)5.1965343
Kurtosis90.090798
Mean2.8614361 × 1010
Median Absolute Deviation (MAD)1.0305394 × 109
Skewness8.9192111
Sum4.1776966 × 1012
Variance2.2110354 × 1022
MonotonicityNot monotonic
2023-12-13T08:49:05.402014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2
 
1.4%
77050686716 1
 
0.7%
967778980 1
 
0.7%
2742705770 1
 
0.7%
8017450 1
 
0.7%
5840950 1
 
0.7%
32987530 1
 
0.7%
346984000000 1
 
0.7%
37366311950 1
 
0.7%
92497630 1
 
0.7%
Other values (135) 135
91.8%
ValueCountFrequency (%)
0 2
1.4%
2341500 1
0.7%
2425850 1
0.7%
2542750 1
0.7%
2924000 1
0.7%
5840950 1
0.7%
6336970 1
0.7%
8017450 1
0.7%
12690740 1
0.7%
15929000 1
0.7%
ValueCountFrequency (%)
1608110000000 1
0.7%
512634000000 1
0.7%
483171000000 1
0.7%
346984000000 1
0.7%
271448000000 1
0.7%
134345000000 1
0.7%
101376000000 1
0.7%
77050686716 1
0.7%
52897389670 1
0.7%
48477267620 1
0.7%

Interactions

2023-12-13T08:49:03.147800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:02.559410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:02.848188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:03.236768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:02.642880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:02.933735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:03.328390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:02.741673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:49:03.029724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:49:05.502299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사업종류토지_면적(제곱미터)토지_보상금액(원)
순번1.0000.0000.0720.000
사업종류0.0001.0000.1610.193
토지_면적(제곱미터)0.0720.1611.0000.934
토지_보상금액(원)0.0000.1930.9341.000
2023-12-13T08:49:05.601376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번토지_면적(제곱미터)토지_보상금액(원)사업종류
순번1.000-0.139-0.1150.000
토지_면적(제곱미터)-0.1391.0000.8960.069
토지_보상금액(원)-0.1150.8961.0000.158
사업종류0.0000.0690.1581.000

Missing values

2023-12-13T08:49:03.447451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:49:03.534032image/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.
2023-12-13T08:49:03.608487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번사업종류사업명토지_면적(제곱미터)토지_보상금액(원)
01댐부항다목적댐건설사업440913077050686716
12기타이관사업1848443374727120
23수도금강북부급수체계조정(청양계통)981131656357900
34댐용담댐 직하류 하천정비공사820691447288030
45댐충주댐 치수능력증대사업1304646020972710
56수도낙동강중부권급수체계구축사업22818540403000
67댐경인 아라뱃길사업423098101376000000
78수도화순분기 비상연결관로 설치공사66369743400
89수도포천복합화력 용수공급사업9142492149090
910댐굴포천방수로건설사업35387327290
순번사업종류사업명토지_면적(제곱미터)토지_보상금액(원)
137138댐군남홍수조절지건설사업1510886161554100
138139댐횡성댐 직하류 하천정비사업690585789150
139140댐봉화댐건설사업2309816559229510
140141수도태백권광역상수도관로복선화사업55219615600
141142단지시화MTV 광역교통시설 해안로 확장사업298373498035750
142143수도대청댐계통(Ⅲ)광역상수도사업(1차)1162497840601640
143144수도진안계통 급수체계조정사업107722885150
144145댐군위댐 직하류 하천정비공사688822827731000
145146수도대이작도 지하수저류지 설치사업172081652650
146147단지시화MTV 광역교통시설 산단로 확장사업190304480000