Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory752.0 KiB
Average record size in memory77.0 B

Variable types

Categorical4
Text1
Numeric3

Dataset

Description경상북도 울진군 관내 개별공시지가 현황(시군구, 읍면, 리, 구분, 본번, 부번, 지가, 기준월)을 제공합니다.
URLhttps://www.data.go.kr/data/15002787/fileData.do

Alerts

시군구 has constant value ""Constant
기준월 has constant value ""Constant
본번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 본번High correlation
결정지가 is highly skewed (γ1 = 46.60029717)Skewed
부번 has 4847 (48.5%) zerosZeros

Reproduction

Analysis started2023-12-12 15:53:34.192582
Analysis finished2023-12-12 15:53:36.380624
Duration2.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경상북도 울진군
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도 울진군
2nd row경상북도 울진군
3rd row경상북도 울진군
4th row경상북도 울진군
5th row경상북도 울진군

Common Values

ValueCountFrequency (%)
경상북도 울진군 10000
100.0%

Length

2023-12-13T00:53:36.456567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:53:36.568073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 10000
50.0%
울진군 10000
50.0%

읍면
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
울진읍
2009 
기성면
1901 
북면
1847 
온정면
1649 
근남면
1425 
Other values (2)
1169 

Length

Max length3
Median length3
Mean length2.8153
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row근남면
2nd row울진읍
3rd row울진읍
4th row북면
5th row근남면

Common Values

ValueCountFrequency (%)
울진읍 2009
20.1%
기성면 1901
19.0%
북면 1847
18.5%
온정면 1649
16.5%
근남면 1425
14.2%
평해읍 1167
11.7%
죽변면 2
 
< 0.1%

Length

2023-12-13T00:53:36.687227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:53:36.823025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울진읍 2009
20.1%
기성면 1901
19.0%
북면 1847
18.5%
온정면 1649
16.5%
근남면 1425
14.2%
평해읍 1167
11.7%
죽변면 2
 
< 0.1%

리
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T00:53:37.122646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0142
Min length3

Characters and Unicode

Total characters30142
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row산포리
2nd row호월리
3rd row고성리
4th row덕구리
5th row수곡리
ValueCountFrequency (%)
구산리 388
 
3.9%
읍내리 348
 
3.5%
산포리 307
 
3.1%
부구리 304
 
3.0%
덕인리 268
 
2.7%
읍남리 266
 
2.7%
연지리 252
 
2.5%
나곡리 243
 
2.4%
월송리 228
 
2.3%
정명리 223
 
2.2%
Other values (48) 7173
71.7%
2023-12-13T00:53:37.604541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 10000
33.2%
산 1661
 
5.5%
곡 1090
 
3.6%
구 1025
 
3.4%
덕 731
 
2.4%
읍 614
 
2.0%
천 573
 
1.9%
정 569
 
1.9%
인 472
 
1.6%
월 404
 
1.3%
Other values (66) 13003
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30142
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 10000
33.2%
산 1661
 
5.5%
곡 1090
 
3.6%
구 1025
 
3.4%
덕 731
 
2.4%
읍 614
 
2.0%
천 573
 
1.9%
정 569
 
1.9%
인 472
 
1.6%
월 404
 
1.3%
Other values (66) 13003
43.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30142
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 10000
33.2%
산 1661
 
5.5%
곡 1090
 
3.6%
구 1025
 
3.4%
덕 731
 
2.4%
읍 614
 
2.0%
천 573
 
1.9%
정 569
 
1.9%
인 472
 
1.6%
월 404
 
1.3%
Other values (66) 13003
43.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30142
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 10000
33.2%
산 1661
 
5.5%
곡 1090
 
3.6%
구 1025
 
3.4%
덕 731
 
2.4%
읍 614
 
2.0%
천 573
 
1.9%
정 569
 
1.9%
인 472
 
1.6%
월 404
 
1.3%
Other values (66) 13003
43.1%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8587 
2
1413 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 8587
85.9%
2 1413
 
14.1%

Length

2023-12-13T00:53:37.807264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:53:37.959693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8587
85.9%
2 1413
 
14.1%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct1415
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459.0597
Minimum1
Maximum1736
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:53:38.202493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q1148
median391
Q3697
95-th percentile1157
Maximum1736
Range1735
Interquartile range (IQR)549

Descriptive statistics

Standard deviation360.10617
Coefficient of variation (CV)0.784443
Kurtosis-0.040266812
Mean459.0597
Median Absolute Deviation (MAD)263
Skewness0.78469875
Sum4590597
Variance129676.45
MonotonicityNot monotonic
2023-12-13T00:53:38.776563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 49
 
0.5%
14 37
 
0.4%
3 28
 
0.3%
40 27
 
0.3%
109 27
 
0.3%
2 27
 
0.3%
65 27
 
0.3%
108 26
 
0.3%
46 26
 
0.3%
37 26
 
0.3%
Other values (1405) 9700
97.0%
ValueCountFrequency (%)
1 49
0.5%
2 27
0.3%
3 28
0.3%
4 25
0.2%
5 14
 
0.1%
6 21
0.2%
7 22
0.2%
8 20
0.2%
9 19
 
0.2%
10 14
 
0.1%
ValueCountFrequency (%)
1736 1
< 0.1%
1710 2
< 0.1%
1709 1
< 0.1%
1707 1
< 0.1%
1687 1
< 0.1%
1678 1
< 0.1%
1664 1
< 0.1%
1656 1
< 0.1%
1642 1
< 0.1%
1629 1
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct99
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3517
Minimum0
Maximum220
Zeros4847
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:53:39.027335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile14
Maximum220
Range220
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.8594588
Coefficient of variation (CV)2.9416293
Kurtosis130.09893
Mean3.3517
Median Absolute Deviation (MAD)1
Skewness9.3038163
Sum33517
Variance97.208928
MonotonicityNot monotonic
2023-12-13T00:53:39.240898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4847
48.5%
1 1366
 
13.7%
2 1003
 
10.0%
3 615
 
6.2%
4 454
 
4.5%
5 290
 
2.9%
6 209
 
2.1%
7 167
 
1.7%
8 125
 
1.2%
9 116
 
1.2%
Other values (89) 808
 
8.1%
ValueCountFrequency (%)
0 4847
48.5%
1 1366
 
13.7%
2 1003
 
10.0%
3 615
 
6.2%
4 454
 
4.5%
5 290
 
2.9%
6 209
 
2.1%
7 167
 
1.7%
8 125
 
1.2%
9 116
 
1.2%
ValueCountFrequency (%)
220 1
< 0.1%
210 1
< 0.1%
199 1
< 0.1%
188 1
< 0.1%
182 1
< 0.1%
148 1
< 0.1%
146 1
< 0.1%
140 1
< 0.1%
135 1
< 0.1%
133 1
< 0.1%

결정지가
Real number (ℝ)

SKEWED 

Distinct2631
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49938.354
Minimum135
Maximum26900000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:53:39.464882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile675.95
Q13227.5
median9300
Q322500
95-th percentile160025
Maximum26900000
Range26899865
Interquartile range (IQR)19272.5

Descriptive statistics

Standard deviation550177.37
Coefficient of variation (CV)11.017131
Kurtosis2267.8597
Mean49938.354
Median Absolute Deviation (MAD)7360
Skewness46.600297
Sum4.9938354 × 108
Variance3.0269514 × 1011
MonotonicityNot monotonic
2023-12-13T00:53:39.697635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
148000 65
 
0.7%
13000 48
 
0.5%
16000 46
 
0.5%
10500 46
 
0.5%
15600 44
 
0.4%
14000 42
 
0.4%
10400 40
 
0.4%
11500 39
 
0.4%
18000 38
 
0.4%
13500 38
 
0.4%
Other values (2621) 9554
95.5%
ValueCountFrequency (%)
135 1
 
< 0.1%
139 1
 
< 0.1%
141 2
< 0.1%
144 1
 
< 0.1%
145 4
< 0.1%
162 1
 
< 0.1%
169 1
 
< 0.1%
176 1
 
< 0.1%
199 3
< 0.1%
202 1
 
< 0.1%
ValueCountFrequency (%)
26900000 4
< 0.1%
2705000 1
 
< 0.1%
2477000 1
 
< 0.1%
2426000 1
 
< 0.1%
2405000 1
 
< 0.1%
2072000 2
< 0.1%
1988000 1
 
< 0.1%
1810000 1
 
< 0.1%
1565000 1
 
< 0.1%
1414000 1
 
< 0.1%

기준월
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2023-12-13T00:53:39.890049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:53:40.027300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

Interactions

2023-12-13T00:53:35.696370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:34.955994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.344718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.843379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.093834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.463344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.978001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.216616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:53:35.569753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:53:40.129010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면리구분본번부번결정지가
읍면1.0000.9990.0590.2160.1160.037
리0.9991.0000.2110.5180.2340.114
구분0.0590.2111.0000.6990.0360.000
본번0.2160.5180.6991.0000.0470.072
부번0.1160.2340.0360.0471.0000.093
결정지가0.0370.1140.0000.0720.0931.000
2023-12-13T00:53:40.281868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분읍면
구분1.0000.063
읍면0.0631.000
2023-12-13T00:53:40.429678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본번부번결정지가읍면구분
본번1.000-0.0770.1230.1110.545
부번-0.0771.0000.2900.0610.037
결정지가0.1230.2901.0000.0250.000
읍면0.1110.0610.0251.0000.063
구분0.5450.0370.0000.0631.000

Missing values

2023-12-13T00:53:36.149932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:53:36.319792image/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

시군구읍면리구분본번부번결정지가기준월
61581경상북도 울진군근남면산포리11622916001
18691경상북도 울진군울진읍호월리1616299201
12328경상북도 울진군울진읍고성리14431105001
40437경상북도 울진군북면덕구리14591215001
56910경상북도 울진군근남면수곡리267111701
11774경상북도 울진군울진읍고성리11512328001
63358경상북도 울진군근남면산포리111200190001
8277경상북도 울진군울진읍온양리16221560001
8438경상북도 울진군울진읍온양리118701620001
66424경상북도 울진군기성면기성리14362105001
시군구읍면리구분본번부번결정지가기준월
84241경상북도 울진군온정면소태리187211364001
4947경상북도 울진군울진읍읍남리16622108001
99825경상북도 울진군온정면외선미리27205731
91664경상북도 울진군온정면덕인리1848047301
7723경상북도 울진군울진읍연지리17582271001
71819경상북도 울진군기성면방율리1201098201
58897경상북도 울진군근남면구산리11310289501
39962경상북도 울진군북면덕구리112406321
90178경상북도 울진군온정면덕산리11173015401
4724경상북도 울진군울진읍읍남리15423600001