Overview

Dataset statistics

Number of variables3
Number of observations979
Missing cells0
Missing cells (%)0.0%
Duplicate rows147
Duplicate rows (%)15.0%
Total size in memory24.0 KiB
Average record size in memory25.1 B

Variable types

Categorical2
Numeric1

Dataset

Description한국자산관리공사_국유재산 지적측량 현황("측량의뢰년월","지역","건수") 데이터 제공
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15074533/fileData.do

Alerts

Dataset has 147 (15.0%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 23:49:34.382335
Analysis finished2023-12-12 23:49:34.638704
Duration0.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측량의뢰년월
Categorical

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2014-09
136 
2014-08
131 
2014-07
123 
2014-04
118 
2014-05
109 
Other values (5)
362 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014-03
2nd row2014-03
3rd row2014-03
4th row2014-03
5th row2014-03

Common Values

ValueCountFrequency (%)
2014-09 136
13.9%
2014-08 131
13.4%
2014-07 123
12.6%
2014-04 118
12.1%
2014-05 109
11.1%
2014-10 104
10.6%
2014-06 101
10.3%
2014-11 90
9.2%
2014-12 59
6.0%
2014-03 8
 
0.8%

Length

2023-12-13T08:49:34.685411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:49:34.781170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2014-09 136
13.9%
2014-08 131
13.4%
2014-07 123
12.6%
2014-04 118
12.1%
2014-05 109
11.1%
2014-10 104
10.6%
2014-06 101
10.3%
2014-11 90
9.2%
2014-12 59
6.0%
2014-03 8
 
0.8%

지역
Categorical

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
경기
160 
부산
152 
경남
152 
전남
109 
경북
77 
Other values (11)
329 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산
2nd row경기
3rd row경북
4th row경남
5th row경남

Common Values

ValueCountFrequency (%)
경기 160
16.3%
부산 152
15.5%
경남 152
15.5%
전남 109
11.1%
경북 77
7.9%
서울 74
7.6%
강원 49
 
5.0%
전북 41
 
4.2%
울산 36
 
3.7%
충남 33
 
3.4%
Other values (6) 96
9.8%

Length

2023-12-13T08:49:34.895086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 160
16.3%
부산 152
15.5%
경남 152
15.5%
전남 109
11.1%
경북 77
7.9%
서울 74
7.6%
강원 49
 
5.0%
전북 41
 
4.2%
울산 36
 
3.7%
충남 33
 
3.4%
Other values (6) 96
9.8%

건수
Real number (ℝ)

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3003064
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.7 KiB
2023-12-13T08:49:34.996455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum12
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.89973292
Coefficient of variation (CV)0.69193915
Kurtosis40.95958
Mean1.3003064
Median Absolute Deviation (MAD)0
Skewness5.4246303
Sum1273
Variance0.80951933
MonotonicityNot monotonic
2023-12-13T08:49:35.089492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 806
82.3%
2 118
 
12.1%
3 30
 
3.1%
4 11
 
1.1%
7 5
 
0.5%
5 4
 
0.4%
6 2
 
0.2%
9 2
 
0.2%
12 1
 
0.1%
ValueCountFrequency (%)
1 806
82.3%
2 118
 
12.1%
3 30
 
3.1%
4 11
 
1.1%
5 4
 
0.4%
6 2
 
0.2%
7 5
 
0.5%
9 2
 
0.2%
12 1
 
0.1%
ValueCountFrequency (%)
12 1
 
0.1%
9 2
 
0.2%
7 5
 
0.5%
6 2
 
0.2%
5 4
 
0.4%
4 11
 
1.1%
3 30
 
3.1%
2 118
 
12.1%
1 806
82.3%

Interactions

2023-12-13T08:49:34.464939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:49:35.165629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측량의뢰년월지역건수
측량의뢰년월1.0000.1520.000
지역0.1521.0000.210
건수0.0000.2101.000
2023-12-13T08:49:35.253780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역측량의뢰년월
지역1.0000.060
측량의뢰년월0.0601.000
2023-12-13T08:49:35.327562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건수측량의뢰년월지역
건수1.0000.0000.075
측량의뢰년월0.0001.0000.060
지역0.0750.0601.000

Missing values

2023-12-13T08:49:34.557603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:49:34.614929image/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

측량의뢰년월지역건수
02014-03부산1
12014-03경기1
22014-03경북1
32014-03경남1
42014-03경남1
52014-03경남1
62014-03경남1
72014-03경남1
82014-04서울1
92014-04서울1
측량의뢰년월지역건수
9692014-12경북1
9702014-12경남1
9712014-12경남1
9722014-12경남2
9732014-12경남1
9742014-12경남2
9752014-12경남1
9762014-12경남2
9772014-12경남1
9782014-12경남1

Duplicate rows

Most frequently occurring

측량의뢰년월지역건수# duplicates
672014-08경기126
832014-09경기125
492014-07경기121
32014-04경남119
382014-06경남118
632014-07전남118
682014-08경남117
22014-04경기116
772014-08전남116
232014-05경남115