Overview

Dataset statistics

Number of variables7
Number of observations1043
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.2 KiB
Average record size in memory59.1 B

Variable types

Numeric3
Text1
Boolean1
Categorical2

Dataset

Description예산군 공유재산 현황(소재지, 대부가능여부, 토지지목, 실지목, 면적등)에 대한 정보
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=408&beforeMenuCd=DOM_000000201001001000&publicdatapk=15040820

Alerts

면적 is highly overall correlated with 실면적High correlation
실면적 is highly overall correlated with 면적High correlation
대부가능여부 is highly overall correlated with 실지목코드High correlation
토지지목코드 is highly overall correlated with 실지목코드High correlation
실지목코드 is highly overall correlated with 대부가능여부 and 1 other fieldsHigh correlation
면적 is highly skewed (γ1 = 28.30002091)Skewed
실면적 is highly skewed (γ1 = 28.3033214)Skewed
순번 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:56:33.644272
Analysis finished2024-01-09 22:56:35.316947
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1043
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean522
Minimum1
Maximum1043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2024-01-10T07:56:35.385364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile53.1
Q1261.5
median522
Q3782.5
95-th percentile990.9
Maximum1043
Range1042
Interquartile range (IQR)521

Descriptive statistics

Standard deviation301.23247
Coefficient of variation (CV)0.57707369
Kurtosis-1.2
Mean522
Median Absolute Deviation (MAD)261
Skewness0
Sum544446
Variance90741
MonotonicityStrictly increasing
2024-01-10T07:56:35.509190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
687 1
 
0.1%
689 1
 
0.1%
690 1
 
0.1%
691 1
 
0.1%
692 1
 
0.1%
693 1
 
0.1%
694 1
 
0.1%
695 1
 
0.1%
696 1
 
0.1%
Other values (1033) 1033
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1043 1
0.1%
1042 1
0.1%
1041 1
0.1%
1040 1
0.1%
1039 1
0.1%
1038 1
0.1%
1037 1
0.1%
1036 1
0.1%
1035 1
0.1%
1034 1
0.1%

소재지
Text

UNIQUE 

Distinct1043
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2024-01-10T07:56:35.739030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length23.247363
Min length19

Characters and Unicode

Total characters24247
Distinct characters121
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

Unique1043 ?
Unique (%)100.0%

Sample

1st row충청남도 예산군 예산읍 예산리 4-1
2nd row충청남도 예산군 예산읍 예산리 5-1
3rd row충청남도 예산군 예산읍 예산리 288-6
4th row충청남도 예산군 예산읍 예산리 288-16
5th row충청남도 예산군 예산읍 예산리 296-2
ValueCountFrequency (%)
충청남도 1043
19.5%
예산군 1043
19.5%
신암면 251
 
4.7%
조곡리 182
 
3.4%
예산읍 126
 
2.4%
124
 
2.3%
오가면 100
 
1.9%
고덕면 92
 
1.7%
삽교읍 92
 
1.7%
대흥면 83
 
1.6%
Other values (1119) 2203
41.3%
2024-01-10T07:56:36.091587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5359
22.1%
1488
 
6.1%
1211
 
5.0%
1067
 
4.4%
1043
 
4.3%
1043
 
4.3%
1043
 
4.3%
1043
 
4.3%
1043
 
4.3%
- 981
 
4.0%
Other values (111) 8926
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13658
56.3%
Space Separator 5359
 
22.1%
Decimal Number 4249
 
17.5%
Dash Punctuation 981
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1488
10.9%
1211
 
8.9%
1067
 
7.8%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
825
 
6.0%
429
 
3.1%
Other values (99) 3423
25.1%
Decimal Number
ValueCountFrequency (%)
1 850
20.0%
2 591
13.9%
4 569
13.4%
3 556
13.1%
9 334
 
7.9%
5 291
 
6.8%
7 279
 
6.6%
6 276
 
6.5%
8 258
 
6.1%
0 245
 
5.8%
Space Separator
ValueCountFrequency (%)
5359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 981
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13658
56.3%
Common 10589
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1488
10.9%
1211
 
8.9%
1067
 
7.8%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
825
 
6.0%
429
 
3.1%
Other values (99) 3423
25.1%
Common
ValueCountFrequency (%)
5359
50.6%
- 981
 
9.3%
1 850
 
8.0%
2 591
 
5.6%
4 569
 
5.4%
3 556
 
5.3%
9 334
 
3.2%
5 291
 
2.7%
7 279
 
2.6%
6 276
 
2.6%
Other values (2) 503
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13658
56.3%
ASCII 10589
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5359
50.6%
- 981
 
9.3%
1 850
 
8.0%
2 591
 
5.6%
4 569
 
5.4%
3 556
 
5.3%
9 334
 
3.2%
5 291
 
2.7%
7 279
 
2.6%
6 276
 
2.6%
Other values (2) 503
 
4.8%
Hangul
ValueCountFrequency (%)
1488
10.9%
1211
 
8.9%
1067
 
7.8%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
1043
 
7.6%
825
 
6.0%
429
 
3.1%
Other values (99) 3423
25.1%

대부가능여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
True
781 
False
262 
ValueCountFrequency (%)
True 781
74.9%
False 262
 
25.1%
2024-01-10T07:56:36.193581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

토지지목코드
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
480 
임야
210 
143 
132 
도로
 
24
Other values (9)
54 

Length

Max length4
Median length1
Mean length1.3173538
Min length1

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row학교용지
2nd row학교용지
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
480
46.0%
임야 210
20.1%
143
 
13.7%
132
 
12.7%
도로 24
 
2.3%
잡종지 13
 
1.2%
학교용지 11
 
1.1%
유지 10
 
1.0%
구거 7
 
0.7%
과수원 5
 
0.5%
Other values (4) 8
 
0.8%

Length

2024-01-10T07:56:36.292984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
480
46.0%
임야 210
20.1%
143
 
13.7%
132
 
12.7%
도로 24
 
2.3%
잡종지 13
 
1.2%
학교용지 11
 
1.1%
유지 10
 
1.0%
구거 7
 
0.7%
과수원 5
 
0.5%
Other values (4) 8
 
0.8%

실지목코드
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
453 
임야
240 
124 
110 
잡종지
 
43
Other values (12)
73 

Length

Max length4
Median length1
Mean length1.4161074
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row
2nd row임야
3rd row
4th row
5th row임야

Common Values

ValueCountFrequency (%)
453
43.4%
임야 240
23.0%
124
 
11.9%
110
 
10.5%
잡종지 43
 
4.1%
도로 29
 
2.8%
과수원 12
 
1.2%
구거 10
 
1.0%
학교용지 6
 
0.6%
하천 3
 
0.3%
Other values (7) 13
 
1.2%

Length

2024-01-10T07:56:36.437150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
453
43.4%
임야 240
23.0%
124
 
11.9%
110
 
10.5%
잡종지 43
 
4.1%
도로 29
 
2.8%
과수원 12
 
1.2%
구거 10
 
1.0%
학교용지 6
 
0.6%
하천 3
 
0.3%
Other values (7) 13
 
1.2%

면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct737
Distinct (%)70.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2217.392
Minimum2
Maximum685801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2024-01-10T07:56:36.587436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile23
Q1163.5
median437
Q31091
95-th percentile4964.2
Maximum685801
Range685799
Interquartile range (IQR)927.5

Descriptive statistics

Standard deviation22245.083
Coefficient of variation (CV)10.032093
Kurtosis859.84739
Mean2217.392
Median Absolute Deviation (MAD)338
Skewness28.300021
Sum2312739.9
Variance4.9484372 × 108
MonotonicityNot monotonic
2024-01-10T07:56:36.712902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 11
 
1.1%
99.0 11
 
1.1%
298.0 9
 
0.9%
139.0 6
 
0.6%
79.0 6
 
0.6%
1091.0 5
 
0.5%
10.0 5
 
0.5%
46.0 5
 
0.5%
992.0 5
 
0.5%
102.0 5
 
0.5%
Other values (727) 975
93.5%
ValueCountFrequency (%)
2.0 4
0.4%
2.7 1
 
0.1%
3.0 1
 
0.1%
3.8 1
 
0.1%
4.0 3
0.3%
5.0 4
0.4%
6.0 4
0.4%
7.9 1
 
0.1%
8.0 2
0.2%
9.0 1
 
0.1%
ValueCountFrequency (%)
685801.0 1
0.1%
136583.0 1
0.1%
120142.0 1
0.1%
58196.0 1
0.1%
52715.0 1
0.1%
39669.0 1
0.1%
32714.0 1
0.1%
31690.0 1
0.1%
31102.0 1
0.1%
29770.0 1
0.1%

실면적
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct741
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2211.5149
Minimum2
Maximum685801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.3 KiB
2024-01-10T07:56:36.833691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile23
Q1163.5
median437
Q31086.5
95-th percentile4921
Maximum685801
Range685799
Interquartile range (IQR)923

Descriptive statistics

Standard deviation22244.422
Coefficient of variation (CV)10.058454
Kurtosis859.98006
Mean2211.5149
Median Absolute Deviation (MAD)338
Skewness28.303321
Sum2306610.1
Variance4.9481429 × 108
MonotonicityNot monotonic
2024-01-10T07:56:36.997797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 11
 
1.1%
198.0 11
 
1.1%
298.0 9
 
0.9%
79.0 6
 
0.6%
139.0 6
 
0.6%
1091.0 5
 
0.5%
31.0 5
 
0.5%
992.0 5
 
0.5%
132.0 5
 
0.5%
46.0 5
 
0.5%
Other values (731) 975
93.5%
ValueCountFrequency (%)
2.0 4
0.4%
2.7 1
 
0.1%
3.0 1
 
0.1%
3.8 1
 
0.1%
4.0 3
0.3%
5.0 4
0.4%
6.0 4
0.4%
6.77 1
 
0.1%
7.9 1
 
0.1%
8.0 2
0.2%
ValueCountFrequency (%)
685801.0 1
0.1%
136583.0 1
0.1%
120142.0 1
0.1%
58196.0 1
0.1%
52715.0 1
0.1%
39669.0 1
0.1%
32714.0 1
0.1%
31690.0 1
0.1%
31102.0 1
0.1%
29770.0 1
0.1%

Interactions

2024-01-10T07:56:34.831576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.028921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.283168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.918419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.107022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.374926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:35.015098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.191166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:56:34.739480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:56:37.114423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대부가능여부토지지목코드실지목코드면적실면적
순번1.0000.4450.4480.4610.0000.000
대부가능여부0.4451.0000.3380.5700.0000.000
토지지목코드0.4480.3381.0000.9330.0000.000
실지목코드0.4610.5700.9331.0000.0000.000
면적0.0000.0000.0000.0001.0001.000
실면적0.0000.0000.0000.0001.0001.000
2024-01-10T07:56:37.228724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토지지목코드대부가능여부실지목코드
토지지목코드1.0000.2630.677
대부가능여부0.2631.0000.512
실지목코드0.6770.5121.000
2024-01-10T07:56:37.326186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적실면적대부가능여부토지지목코드실지목코드
순번1.0000.0520.0530.3400.1980.198
면적0.0521.0001.0000.0000.0000.000
실면적0.0531.0001.0000.0000.0000.000
대부가능여부0.3400.0000.0001.0000.2630.512
토지지목코드0.1980.0000.0000.2631.0000.677
실지목코드0.1980.0000.0000.5120.6771.000

Missing values

2024-01-10T07:56:35.165476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:56:35.275752image/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

순번소재지대부가능여부토지지목코드실지목코드면적실면적
01충청남도 예산군 예산읍 예산리 4-1Y학교용지1144.01144.0
12충청남도 예산군 예산읍 예산리 5-1N학교용지임야681.0681.0
23충청남도 예산군 예산읍 예산리 288-6Y21.021.0
34충청남도 예산군 예산읍 예산리 288-16N6.06.0
45충청남도 예산군 예산읍 예산리 296-2N임야47.047.0
56충청남도 예산군 예산읍 예산리 298-7N임야5.05.0
67충청남도 예산군 예산읍 예산리 303-17Y71.071.0
78충청남도 예산군 예산읍 예산리 320-1Y310.0310.0
89충청남도 예산군 예산읍 예산리 320-2Y156.0156.0
910충청남도 예산군 예산읍 예산리 320-3Y374.0374.0
순번소재지대부가능여부토지지목코드실지목코드면적실면적
10331034충청남도 예산군 오가면 오촌리 10-40Y1170.01170.0
10341035충청남도 예산군 오가면 오촌리 10-41Y묘지1148.01148.0
10351036충청남도 예산군 오가면 오촌리 10-42Y묘지730.0730.0
10361037충청남도 예산군 오가면 오촌리 10-43Y373.0373.0
10371038충청남도 예산군 오가면 오촌리 10-44Y365.0365.0
10381039충청남도 예산군 오가면 오촌리 10-45Y3732.03732.0
10391040충청남도 예산군 오가면 오촌리 10-46Y3091.03091.0
10401041충청남도 예산군 오가면 오촌리 10-73Y임야임야3691.03691.0
10411042충청남도 예산군 오가면 오촌리 89-3Y79.079.0
10421043충청남도 예산군 오가면 오촌리 산 24-5N임야임야1091.01091.0