Overview

Dataset statistics

Number of variables7
Number of observations2570
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory145.7 KiB
Average record size in memory58.1 B

Variable types

Text1
DateTime1
Categorical3
Numeric2

Dataset

Description군유림현황으로 소재지, 취득일자, 토지지목코드, 실지목코드, 면적, 실면적, 데이터기준일을 포함하여 제공하고 있습니다.
Author충청북도 단양군
URLhttps://www.data.go.kr/data/3072356/fileData.do

Alerts

토지지목코드 has constant value ""Constant
데이터기준일 has constant value ""Constant
면적(제곱미터) is highly overall correlated with 실면적(제곱미터)High correlation
실면적(제곱미터) is highly overall correlated with 면적(제곱미터)High correlation
실지목코드 is highly imbalanced (67.5%)Imbalance
면적(제곱미터) is highly skewed (γ1 = 22.45140865)Skewed
실면적(제곱미터) is highly skewed (γ1 = 22.45092405)Skewed
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:55:16.537256
Analysis finished2023-12-12 12:55:17.507345
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소재지
Text

UNIQUE 

Distinct2570
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.2 KiB
2023-12-12T21:55:17.895787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length23.497276
Min length20

Characters and Unicode

Total characters60388
Distinct characters117
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

Unique2570 ?
Unique (%)100.0%

Sample

1st row충청북도 단양군 단양읍 현천리 산 28
2nd row충청북도 단양군 단양읍 현천리 산 28-1
3rd row충청북도 단양군 단양읍 현천리 산 32
4th row충청북도 단양군 단양읍 덕상리 산 11
5th row충청북도 단양군 단양읍 덕상리 산 14
ValueCountFrequency (%)
충청북도 2570
17.2%
단양군 2570
17.2%
산 2089
 
14.0%
적성면 426
 
2.9%
영춘면 415
 
2.8%
단양읍 388
 
2.6%
대강면 317
 
2.1%
어상천면 292
 
2.0%
가곡면 274
 
1.8%
매포읍 264
 
1.8%
Other values (1633) 5334
35.7%
2023-12-12T21:55:18.534386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14944
24.7%
단 3152
 
5.2%
양 2990
 
5.0%
북 2609
 
4.3%
도 2597
 
4.3%
충 2570
 
4.3%
리 2570
 
4.3%
군 2570
 
4.3%
청 2570
 
4.3%
산 2176
 
3.6%
Other values (107) 21640
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35708
59.1%
Space Separator 14944
24.7%
Decimal Number 7781
 
12.9%
Dash Punctuation 1955
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 3152
 
8.8%
양 2990
 
8.4%
북 2609
 
7.3%
도 2597
 
7.3%
충 2570
 
7.2%
리 2570
 
7.2%
군 2570
 
7.2%
청 2570
 
7.2%
산 2176
 
6.1%
면 1918
 
5.4%
Other values (95) 9986
28.0%
Decimal Number
ValueCountFrequency (%)
1 1722
22.1%
2 1080
13.9%
3 906
11.6%
4 774
9.9%
5 649
 
8.3%
6 592
 
7.6%
7 584
 
7.5%
8 526
 
6.8%
9 501
 
6.4%
0 447
 
5.7%
Space Separator
ValueCountFrequency (%)
14944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1955
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35708
59.1%
Common 24680
40.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 3152
 
8.8%
양 2990
 
8.4%
북 2609
 
7.3%
도 2597
 
7.3%
충 2570
 
7.2%
리 2570
 
7.2%
군 2570
 
7.2%
청 2570
 
7.2%
산 2176
 
6.1%
면 1918
 
5.4%
Other values (95) 9986
28.0%
Common
ValueCountFrequency (%)
14944
60.6%
- 1955
 
7.9%
1 1722
 
7.0%
2 1080
 
4.4%
3 906
 
3.7%
4 774
 
3.1%
5 649
 
2.6%
6 592
 
2.4%
7 584
 
2.4%
8 526
 
2.1%
Other values (2) 948
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35708
59.1%
ASCII 24680
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14944
60.6%
- 1955
 
7.9%
1 1722
 
7.0%
2 1080
 
4.4%
3 906
 
3.7%
4 774
 
3.1%
5 649
 
2.6%
6 592
 
2.4%
7 584
 
2.4%
8 526
 
2.1%
Other values (2) 948
 
3.8%
Hangul
ValueCountFrequency (%)
단 3152
 
8.8%
양 2990
 
8.4%
북 2609
 
7.3%
도 2597
 
7.3%
충 2570
 
7.2%
리 2570
 
7.2%
군 2570
 
7.2%
청 2570
 
7.2%
산 2176
 
6.1%
면 1918
 
5.4%
Other values (95) 9986
28.0%

취득일자
Date

Distinct722
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Memory size20.2 KiB
Minimum1918-07-10 00:00:00
Maximum2020-10-26 00:00:00
2023-12-12T21:55:18.696616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:55:18.839999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

토지지목코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.2 KiB
05-임야
2570 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05-임야
2nd row05-임야
3rd row05-임야
4th row05-임야
5th row05-임야

Common Values

ValueCountFrequency (%)
05-임야 2570
100.0%

Length

2023-12-12T21:55:18.975136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:55:19.066918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05-임야 2570
100.0%

실지목코드
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size20.2 KiB
05-임야
1948 
14-도로
319 
28-잡종지
 
161
17-하천
 
80
01-전
 
22
Other values (10)
 
40

Length

Max length7
Median length5
Mean length5.051751
Min length4

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row05-임야
2nd row05-임야
3rd row05-임야
4th row05-임야
5th row05-임야

Common Values

ValueCountFrequency (%)
05-임야 1948
75.8%
14-도로 319
 
12.4%
28-잡종지 161
 
6.3%
17-하천 80
 
3.1%
01-전 22
 
0.9%
08-대 21
 
0.8%
22-공원 5
 
0.2%
10-학교용지 5
 
0.2%
18-구거 2
 
0.1%
27-묘지 2
 
0.1%
Other values (5) 5
 
0.2%

Length

2023-12-12T21:55:19.189214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
05-임야 1948
75.8%
14-도로 319
 
12.4%
28-잡종지 161
 
6.3%
17-하천 80
 
3.1%
01-전 22
 
0.9%
08-대 21
 
0.8%
22-공원 5
 
0.2%
10-학교용지 5
 
0.2%
18-구거 2
 
0.1%
27-묘지 2
 
0.1%
Other values (5) 5
 
0.2%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1715
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35473.528
Minimum1.7
Maximum6545058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2023-12-12T21:55:19.323646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile34
Q1234.25
median1088
Q311476.75
95-th percentile169491.95
Maximum6545058
Range6545056.3
Interquartile range (IQR)11242.5

Descriptive statistics

Standard deviation178689.14
Coefficient of variation (CV)5.0372532
Kurtosis727.35548
Mean35473.528
Median Absolute Deviation (MAD)1025.5
Skewness22.451409
Sum91166966
Variance3.1929809 × 1010
MonotonicityNot monotonic
2023-12-12T21:55:19.467452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 11
 
0.4%
496.0 11
 
0.4%
198.0 9
 
0.4%
66.0 9
 
0.4%
24.0 8
 
0.3%
73.0 8
 
0.3%
96.0 8
 
0.3%
2380.0 8
 
0.3%
893.0 8
 
0.3%
59.0 7
 
0.3%
Other values (1705) 2483
96.6%
ValueCountFrequency (%)
1.7 1
 
< 0.1%
2.0 2
 
0.1%
3.0 11
0.4%
4.0 3
 
0.1%
5.0 5
0.2%
6.0 4
 
0.2%
7.0 3
 
0.1%
8.0 3
 
0.1%
9.0 4
 
0.2%
10.0 4
 
0.2%
ValueCountFrequency (%)
6545058.0 1
< 0.1%
2732407.0 1
< 0.1%
2652298.0 1
< 0.1%
1339240.0 1
< 0.1%
1186215.0 1
< 0.1%
1001653.0 1
< 0.1%
987372.0 1
< 0.1%
985548.0 1
< 0.1%
950380.0 1
< 0.1%
900099.0 1
< 0.1%

실면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1713
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35463.187
Minimum1.7
Maximum6545058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size22.7 KiB
2023-12-12T21:55:19.644906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile34
Q1234.25
median1074.5
Q311307.5
95-th percentile169491.95
Maximum6545058
Range6545056.3
Interquartile range (IQR)11073.25

Descriptive statistics

Standard deviation178690.87
Coefficient of variation (CV)5.0387709
Kurtosis727.33235
Mean35463.187
Median Absolute Deviation (MAD)1011.5
Skewness22.450924
Sum91140391
Variance3.1930429 × 1010
MonotonicityNot monotonic
2023-12-12T21:55:19.789352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
496.0 11
 
0.4%
3.0 11
 
0.4%
198.0 9
 
0.4%
66.0 9
 
0.4%
893.0 8
 
0.3%
73.0 8
 
0.3%
96.0 8
 
0.3%
24.0 8
 
0.3%
2380.0 8
 
0.3%
102.0 7
 
0.3%
Other values (1703) 2483
96.6%
ValueCountFrequency (%)
1.7 1
 
< 0.1%
2.0 2
 
0.1%
3.0 11
0.4%
4.0 3
 
0.1%
5.0 5
0.2%
6.0 4
 
0.2%
7.0 3
 
0.1%
8.0 3
 
0.1%
9.0 4
 
0.2%
10.0 4
 
0.2%
ValueCountFrequency (%)
6545058.0 1
< 0.1%
2732407.0 1
< 0.1%
2652298.0 1
< 0.1%
1339240.0 1
< 0.1%
1186215.0 1
< 0.1%
1001653.0 1
< 0.1%
987372.0 1
< 0.1%
985548.0 1
< 0.1%
950380.0 1
< 0.1%
900099.0 1
< 0.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.2 KiB
2022-10-30
2570 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-30
2nd row2022-10-30
3rd row2022-10-30
4th row2022-10-30
5th row2022-10-30

Common Values

ValueCountFrequency (%)
2022-10-30 2570
100.0%

Length

2023-12-12T21:55:19.934942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:55:20.027735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-30 2570
100.0%

Interactions

2023-12-12T21:55:17.021232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:55:16.808858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:55:17.131666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:55:16.915303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:55:20.092411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실지목코드면적(제곱미터)실면적(제곱미터)
실지목코드1.0000.0000.000
면적(제곱미터)0.0001.0001.000
실면적(제곱미터)0.0001.0001.000
2023-12-12T21:55:20.190232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)실면적(제곱미터)실지목코드
면적(제곱미터)1.0000.9990.000
실면적(제곱미터)0.9991.0000.000
실지목코드0.0000.0001.000

Missing values

2023-12-12T21:55:17.292470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:55:17.445256image/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

소재지취득일자토지지목코드실지목코드면적(제곱미터)실면적(제곱미터)데이터기준일
0충청북도 단양군 단양읍 현천리 산 281963-01-1605-임야05-임야22999.022999.02022-10-30
1충청북도 단양군 단양읍 현천리 산 28-11963-01-1605-임야05-임야2670.02670.02022-10-30
2충청북도 단양군 단양읍 현천리 산 321963-01-1605-임야05-임야6844.06844.02022-10-30
3충청북도 단양군 단양읍 덕상리 산 111963-01-1605-임야05-임야5950.05950.02022-10-30
4충청북도 단양군 단양읍 덕상리 산 141963-01-1605-임야05-임야413073.0413073.02022-10-30
5충청북도 단양군 단양읍 덕상리 산 211963-01-1605-임야05-임야75769.075769.02022-10-30
6충청북도 단양군 단양읍 덕상리 산 401963-01-1605-임야05-임야34512.034512.02022-10-30
7충청북도 단양군 단양읍 덕상리 산 441963-01-1605-임야05-임야2329.02329.02022-10-30
8충청북도 단양군 단양읍 덕상리 산 461963-01-1605-임야05-임야1190.01190.02022-10-30
9충청북도 단양군 단양읍 심곡리 산 1-61984-08-1805-임야05-임야124.0124.02022-10-30
소재지취득일자토지지목코드실지목코드면적(제곱미터)실면적(제곱미터)데이터기준일
2560충청북도 단양군 단성면 대잠리 산 561963-01-1605-임야05-임야1587.01587.02022-10-30
2561충청북도 단양군 단성면 대잠리 산 582003-05-0905-임야05-임야29355.029355.02022-10-30
2562충청북도 단양군 단성면 대잠리 산 602005-05-1605-임야28-잡종지107640.0107640.02022-10-30
2563충청북도 단양군 단성면 대잠리 산 611963-01-1605-임야05-임야35271.035271.02022-10-30
2564충청북도 단양군 단성면 대잠리 산 631963-01-1605-임야05-임야110050.0110050.02022-10-30
2565충청북도 단양군 단성면 대잠리 산 642005-05-2705-임야28-잡종지987372.0987372.02022-10-30
2566충청북도 단양군 단성면 대잠리 산 791963-01-1605-임야05-임야14579.014579.02022-10-30
2567충청북도 단양군 단성면 대잠리 산 911963-01-1605-임야05-임야2083.02083.02022-10-30
2568충청북도 단양군 단성면 대잠리 산 921963-01-1605-임야05-임야199835.0199835.02022-10-30
2569충청북도 단양군 단성면 대잠리 산 1041963-01-1605-임야05-임야6347.06347.02022-10-30