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

Categorical3
Text1
Numeric3
Boolean1

Dataset

Description전주시 내 구별(완산구, 덕진구) 공시지가 현황입니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=5&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15008421

Alerts

기준년도 has constant value ""Constant
기준월 has constant value ""Constant
표준지여부 is highly imbalanced (81.7%)Imbalance
부번 has 1124 (11.2%) zerosZeros

Reproduction

Analysis started2024-03-14 01:19:35.131629
Analysis finished2024-03-14 01:19:36.765954
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
완산구
6881 
덕진구
3119 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완산구
2nd row완산구
3rd row완산구
4th row완산구
5th row덕진구

Common Values

ValueCountFrequency (%)
완산구 6881
68.8%
덕진구 3119
31.2%

Length

2024-03-14T10:19:36.812873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:36.886464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완산구 6881
68.8%
덕진구 3119
31.2%

읍면동
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T10:19:37.052411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.167
Min length2

Characters and Unicode

Total characters41670
Distinct characters53
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row중앙동3가
2nd row태평동
3rd row효자동1가
4th row남노송동
5th row인후동1가
ValueCountFrequency (%)
인후동1가 540
 
5.4%
금암동 505
 
5.1%
효자동3가 440
 
4.4%
진북동 384
 
3.8%
중노송동 368
 
3.7%
삼천동3가 353
 
3.5%
중화산동2가 346
 
3.5%
효자동1가 330
 
3.3%
중인동 330
 
3.3%
금상동 309
 
3.1%
Other values (48) 6095
61.0%
2024-03-14T10:19:37.424409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10340
24.8%
가 5156
 
12.4%
1 1914
 
4.6%
2 1869
 
4.5%
서 1301
 
3.1%
3 1212
 
2.9%
중 1164
 
2.8%
인 1145
 
2.7%
효 1044
 
2.5%
자 1044
 
2.5%
Other values (43) 15481
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36618
87.9%
Decimal Number 5052
 
12.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10340
28.2%
가 5156
14.1%
서 1301
 
3.6%
중 1164
 
3.2%
인 1145
 
3.1%
효 1044
 
2.9%
자 1044
 
2.9%
산 901
 
2.5%
화 871
 
2.4%
진 821
 
2.2%
Other values (39) 12831
35.0%
Decimal Number
ValueCountFrequency (%)
1 1914
37.9%
2 1869
37.0%
3 1212
24.0%
4 57
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36618
87.9%
Common 5052
 
12.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10340
28.2%
가 5156
14.1%
서 1301
 
3.6%
중 1164
 
3.2%
인 1145
 
3.1%
효 1044
 
2.9%
자 1044
 
2.9%
산 901
 
2.5%
화 871
 
2.4%
진 821
 
2.2%
Other values (39) 12831
35.0%
Common
ValueCountFrequency (%)
1 1914
37.9%
2 1869
37.0%
3 1212
24.0%
4 57
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36618
87.9%
ASCII 5052
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10340
28.2%
가 5156
14.1%
서 1301
 
3.6%
중 1164
 
3.2%
인 1145
 
3.1%
효 1044
 
2.9%
자 1044
 
2.9%
산 901
 
2.5%
화 871
 
2.4%
진 821
 
2.2%
Other values (39) 12831
35.0%
ASCII
ValueCountFrequency (%)
1 1914
37.9%
2 1869
37.0%
3 1212
24.0%
4 57
 
1.1%

본번
Real number (ℝ)

Distinct1468
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean514.0856
Minimum1
Maximum1735
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T10:19:37.617618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25
Q1164
median401
Q3746
95-th percentile1522
Maximum1735
Range1734
Interquartile range (IQR)582

Descriptive statistics

Standard deviation432.54424
Coefficient of variation (CV)0.84138563
Kurtosis0.17814366
Mean514.0856
Median Absolute Deviation (MAD)277
Skewness0.96878052
Sum5140856
Variance187094.52
MonotonicityNot monotonic
2024-03-14T10:19:37.756263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167 50
 
0.5%
171 38
 
0.4%
728 38
 
0.4%
8 35
 
0.4%
63 35
 
0.4%
1 33
 
0.3%
4 33
 
0.3%
236 32
 
0.3%
417 32
 
0.3%
322 32
 
0.3%
Other values (1458) 9642
96.4%
ValueCountFrequency (%)
1 33
0.3%
2 24
0.2%
3 11
 
0.1%
4 33
0.3%
5 12
 
0.1%
6 31
0.3%
7 21
0.2%
8 35
0.4%
9 19
0.2%
10 22
0.2%
ValueCountFrequency (%)
1735 1
 
< 0.1%
1734 1
 
< 0.1%
1732 1
 
< 0.1%
1731 2
< 0.1%
1730 3
< 0.1%
1729 3
< 0.1%
1728 4
< 0.1%
1725 1
 
< 0.1%
1721 2
< 0.1%
1720 2
< 0.1%

부번
Real number (ℝ)

ZEROS 

Distinct265
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.6093
Minimum0
Maximum426
Zeros1124
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T10:19:37.866764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q316
95-th percentile79
Maximum426
Range426
Interquartile range (IQR)14

Descriptive statistics

Standard deviation36.136586
Coefficient of variation (CV)2.0521307
Kurtosis28.186533
Mean17.6093
Median Absolute Deviation (MAD)5
Skewness4.6593666
Sum176093
Variance1305.8528
MonotonicityNot monotonic
2024-03-14T10:19:37.973980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1140
 
11.4%
0 1124
 
11.2%
2 765
 
7.6%
3 710
 
7.1%
4 602
 
6.0%
5 505
 
5.1%
6 433
 
4.3%
7 366
 
3.7%
8 348
 
3.5%
9 301
 
3.0%
Other values (255) 3706
37.1%
ValueCountFrequency (%)
0 1124
11.2%
1 1140
11.4%
2 765
7.6%
3 710
7.1%
4 602
6.0%
5 505
5.1%
6 433
 
4.3%
7 366
 
3.7%
8 348
 
3.5%
9 301
 
3.0%
ValueCountFrequency (%)
426 1
< 0.1%
415 1
< 0.1%
389 1
< 0.1%
377 1
< 0.1%
371 1
< 0.1%
370 1
< 0.1%
369 1
< 0.1%
363 1
< 0.1%
350 1
< 0.1%
346 1
< 0.1%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 10000
100.0%

Length

2024-03-14T10:19:38.068313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:38.140719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 10000
100.0%

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

2024-03-14T10:19:38.216657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:38.283225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

공시지가
Real number (ℝ)

Distinct4910
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean425591.32
Minimum544
Maximum7390000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T10:19:38.364044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum544
5-th percentile15500
Q1114900
median332950
Q3543325
95-th percentile1226000
Maximum7390000
Range7389456
Interquartile range (IQR)428425

Descriptive statistics

Standard deviation484450.63
Coefficient of variation (CV)1.1383001
Kurtosis31.332112
Mean425591.32
Median Absolute Deviation (MAD)215450
Skewness4.1698454
Sum4.2559132 × 109
Variance2.3469242 × 1011
MonotonicityNot monotonic
2024-03-14T10:19:38.487517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64500 42
 
0.4%
817800 33
 
0.3%
62500 26
 
0.3%
826100 25
 
0.2%
67000 20
 
0.2%
700300 20
 
0.2%
28500 19
 
0.2%
15000 18
 
0.2%
683000 18
 
0.2%
268200 16
 
0.2%
Other values (4900) 9763
97.6%
ValueCountFrequency (%)
544 1
< 0.1%
867 1
< 0.1%
885 2
< 0.1%
902 1
< 0.1%
1120 1
< 0.1%
1280 1
< 0.1%
1350 2
< 0.1%
1360 1
< 0.1%
1500 1
< 0.1%
1510 1
< 0.1%
ValueCountFrequency (%)
7390000 1
< 0.1%
6801000 1
< 0.1%
6130000 1
< 0.1%
5678000 1
< 0.1%
5590000 1
< 0.1%
5394000 1
< 0.1%
5213000 1
< 0.1%
5187000 1
< 0.1%
5173000 1
< 0.1%
5073000 1
< 0.1%

표준지여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9722 
True
 
278
ValueCountFrequency (%)
False 9722
97.2%
True 278
 
2.8%
2024-03-14T10:19:38.590019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-14T10:19:36.361712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:35.664652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:36.126722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:36.442462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:35.738139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:36.214178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:36.515602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:35.822317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:36.284084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:19:38.641648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구읍면동본번부번공시지가표준지여부
시군구1.0001.0000.2490.1460.1240.016
읍면동1.0001.0000.8040.3160.5300.084
본번0.2490.8041.0000.0960.1680.032
부번0.1460.3160.0961.0000.0000.000
공시지가0.1240.5300.1680.0001.0000.128
표준지여부0.0160.0840.0320.0000.1281.000
2024-03-14T10:19:38.727483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표준지여부시군구
표준지여부1.0000.010
시군구0.0101.000
2024-03-14T10:19:38.817544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본번부번공시지가시군구표준지여부
본번1.0000.0750.1600.1910.025
부번0.0751.0000.2180.1120.000
공시지가0.1600.2181.0000.0950.098
시군구0.1910.1120.0951.0000.010
표준지여부0.0250.0000.0980.0101.000

Missing values

2024-03-14T10:19:36.620353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:19:36.722944image/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

시군구읍면동본번부번기준년도기준월공시지가표준지여부
365완산구중앙동3가462202114824000N
9244완산구태평동223920211361600N
53091완산구효자동1가2164320211405200N
13895완산구남노송동1341220211277200N
73558덕진구인후동1가1778020211348600N
60396완산구효자동3가1612920211737000Y
11692완산구중노송동3952920211508400N
14274완산구남노송동1592920211506800N
47830완산구삼천동2가680020211103300N
61958완산구효자동3가43120211105500N
시군구읍면동본번부번기준년도기준월공시지가표준지여부
95772덕진구산정동874920211895800N
47013완산구삼천동2가415620211108200N
93319덕진구팔복동2가699120211233500N
48538완산구삼천동3가8102021114400N
35345완산구평화동2가21962021159000N
1467완산구경원동3가100020211385200N
90357덕진구금암동16002420211772200N
82600덕진구덕진동1가13603620211333600N
72407덕진구진북동1154120211547700N
93746덕진구팔복동3가60920211225800N