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.항목 : 시군구, 읍면동, 본번, 부번, 기준년도, 기준월, 공시지가, 표준지여부제공부서 : 생태도시계획과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15008421/fileData.do

Alerts

기준년도 has constant value ""Constant
기준월 has constant value ""Constant
표준지여부 is highly imbalanced (82.5%)Imbalance
부번 has 1085 (10.8%) zerosZeros

Reproduction

Analysis started2024-03-14 19:41:53.470636
Analysis finished2024-03-14 19:41:57.099145
Duration3.63 seconds
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
6956 
덕진구
3044 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완산구 6956
69.6%
덕진구 3044
30.4%

Length

2024-03-15T04:41:57.323290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:41:57.666273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완산구 6956
69.6%
덕진구 3044
30.4%

읍면동
Text

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T04:41:58.702083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1894
Min length2

Characters and Unicode

Total characters41894
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 row평화동3가
2nd row다가동4가
3rd row대성동
4th row동서학동
5th row동서학동
ValueCountFrequency (%)
인후동1가 587
 
5.9%
금암동 481
 
4.8%
효자동3가 465
 
4.7%
진북동 389
 
3.9%
중노송동 361
 
3.6%
효자동1가 360
 
3.6%
삼천동3가 348
 
3.5%
중인동 347
 
3.5%
중화산동2가 341
 
3.4%
금상동 275
 
2.8%
Other values (48) 6046
60.5%
2024-03-15T04:41:59.890801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 10320
24.6%
가 5252
 
12.5%
1 1995
 
4.8%
2 1838
 
4.4%
서 1310
 
3.1%
3 1258
 
3.0%
중 1190
 
2.8%
인 1166
 
2.8%
자 1090
 
2.6%
효 1090
 
2.6%
Other values (43) 15385
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36737
87.7%
Decimal Number 5157
 
12.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 10320
28.1%
가 5252
14.3%
서 1310
 
3.6%
중 1190
 
3.2%
인 1166
 
3.2%
자 1090
 
3.0%
효 1090
 
3.0%
화 933
 
2.5%
산 873
 
2.4%
진 829
 
2.3%
Other values (39) 12684
34.5%
Decimal Number
ValueCountFrequency (%)
1 1995
38.7%
2 1838
35.6%
3 1258
24.4%
4 66
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36737
87.7%
Common 5157
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 10320
28.1%
가 5252
14.3%
서 1310
 
3.6%
중 1190
 
3.2%
인 1166
 
3.2%
자 1090
 
3.0%
효 1090
 
3.0%
화 933
 
2.5%
산 873
 
2.4%
진 829
 
2.3%
Other values (39) 12684
34.5%
Common
ValueCountFrequency (%)
1 1995
38.7%
2 1838
35.6%
3 1258
24.4%
4 66
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36737
87.7%
ASCII 5157
 
12.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 10320
28.1%
가 5252
14.3%
서 1310
 
3.6%
중 1190
 
3.2%
인 1166
 
3.2%
자 1090
 
3.0%
효 1090
 
3.0%
화 933
 
2.5%
산 873
 
2.4%
진 829
 
2.3%
Other values (39) 12684
34.5%
ASCII
ValueCountFrequency (%)
1 1995
38.7%
2 1838
35.6%
3 1258
24.4%
4 66
 
1.3%

본번
Real number (ℝ)

Distinct1482
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean509.5798
Minimum1
Maximum1737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T04:42:00.202046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q1162
median398
Q3746
95-th percentile1462.05
Maximum1737
Range1736
Interquartile range (IQR)584

Descriptive statistics

Standard deviation428.57525
Coefficient of variation (CV)0.84103657
Kurtosis0.22040706
Mean509.5798
Median Absolute Deviation (MAD)281
Skewness0.96780479
Sum5095798
Variance183676.74
MonotonicityNot monotonic
2024-03-15T04:42:00.461826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 47
 
0.5%
167 45
 
0.4%
728 42
 
0.4%
4 40
 
0.4%
80 34
 
0.3%
188 33
 
0.3%
322 33
 
0.3%
303 32
 
0.3%
49 30
 
0.3%
50 30
 
0.3%
Other values (1472) 9634
96.3%
ValueCountFrequency (%)
1 47
0.5%
2 30
0.3%
3 22
0.2%
4 40
0.4%
5 16
 
0.2%
6 19
0.2%
7 11
 
0.1%
8 29
0.3%
9 27
0.3%
10 23
0.2%
ValueCountFrequency (%)
1737 1
 
< 0.1%
1735 2
 
< 0.1%
1734 1
 
< 0.1%
1732 1
 
< 0.1%
1729 3
< 0.1%
1728 1
 
< 0.1%
1726 3
< 0.1%
1725 1
 
< 0.1%
1724 2
 
< 0.1%
1721 5
0.1%

부번
Real number (ℝ)

ZEROS 

Distinct265
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.9067
Minimum0
Maximum423
Zeros1085
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T04:42:00.834538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q316
95-th percentile81
Maximum423
Range423
Interquartile range (IQR)14

Descriptive statistics

Standard deviation37.383854
Coefficient of variation (CV)2.087702
Kurtosis28.752778
Mean17.9067
Median Absolute Deviation (MAD)5
Skewness4.7123722
Sum179067
Variance1397.5526
MonotonicityNot monotonic
2024-03-15T04:42:01.211975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1163
 
11.6%
0 1085
 
10.8%
2 846
 
8.5%
3 701
 
7.0%
4 582
 
5.8%
5 466
 
4.7%
7 411
 
4.1%
6 402
 
4.0%
8 355
 
3.5%
9 283
 
2.8%
Other values (255) 3706
37.1%
ValueCountFrequency (%)
0 1085
10.8%
1 1163
11.6%
2 846
8.5%
3 701
7.0%
4 582
5.8%
5 466
4.7%
6 402
 
4.0%
7 411
 
4.1%
8 355
 
3.5%
9 283
 
2.8%
ValueCountFrequency (%)
423 1
< 0.1%
400 1
< 0.1%
398 2
< 0.1%
391 1
< 0.1%
387 1
< 0.1%
381 1
< 0.1%
373 1
< 0.1%
371 1
< 0.1%
364 1
< 0.1%
362 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

2024-03-15T04:42:01.619601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:42:01.975990image/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

2024-03-15T04:42:02.280649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:42:02.475404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

공시지가
Real number (ℝ)

Distinct4941
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean422631
Minimum579
Maximum6801000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T04:42:02.660882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum579
5-th percentile17085
Q1118775
median326550
Q3535750
95-th percentile1221050
Maximum6801000
Range6800421
Interquartile range (IQR)416975

Descriptive statistics

Standard deviation482375.33
Coefficient of variation (CV)1.1413629
Kurtosis30.23906
Mean422631
Median Absolute Deviation (MAD)208400
Skewness4.1699398
Sum4.22631 × 109
Variance2.3268596 × 1011
MonotonicityNot monotonic
2024-03-15T04:42:03.011634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64500 32
 
0.3%
817800 32
 
0.3%
826100 24
 
0.2%
67000 23
 
0.2%
59000 23
 
0.2%
62500 22
 
0.2%
700300 22
 
0.2%
268200 22
 
0.2%
28500 19
 
0.2%
958500 18
 
0.2%
Other values (4931) 9763
97.6%
ValueCountFrequency (%)
579 1
 
< 0.1%
644 1
 
< 0.1%
867 1
 
< 0.1%
875 1
 
< 0.1%
876 4
< 0.1%
885 1
 
< 0.1%
923 1
 
< 0.1%
1150 1
 
< 0.1%
1200 1
 
< 0.1%
1310 1
 
< 0.1%
ValueCountFrequency (%)
6801000 1
< 0.1%
5972000 1
< 0.1%
5729000 1
< 0.1%
5643000 1
< 0.1%
5460000 1
< 0.1%
5405000 1
< 0.1%
5375000 1
< 0.1%
5360000 1
< 0.1%
5337000 1
< 0.1%
5213000 1
< 0.1%

표준지여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9737 
True
 
263
ValueCountFrequency (%)
False 9737
97.4%
True 263
 
2.6%
2024-03-15T04:42:03.316951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-15T04:41:55.495374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:54.022288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:54.671078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:55.793969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:54.319295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:54.852201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:56.043139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:54.488454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:41:55.017440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:42:03.470811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구읍면동본번부번공시지가표준지여부
시군구1.0001.0000.2570.1650.1340.000
읍면동1.0001.0000.8040.3300.5590.088
본번0.2570.8041.0000.1070.2290.043
부번0.1650.3300.1071.0000.0000.000
공시지가0.1340.5590.2290.0001.0000.124
표준지여부0.0000.0880.0430.0000.1241.000
2024-03-15T04:42:03.676471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구표준지여부
시군구1.0000.000
표준지여부0.0001.000
2024-03-15T04:42:03.820811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
본번부번공시지가시군구표준지여부
본번1.0000.0710.1520.1970.033
부번0.0711.0000.2170.1270.000
공시지가0.1520.2171.0000.1030.095
시군구0.1970.1270.1031.0000.000
표준지여부0.0330.0000.0950.0001.000

Missing values

2024-03-15T04:41:56.449076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:41:56.917429image/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
38525완산구평화동3가3002021124000N
4568완산구다가동4가77620211453600N
63155완산구대성동398420211164800N
19093완산구동서학동31552021190700N
19020완산구동서학동3001420211280500N
44237완산구삼천동1가4331420211604800N
57398완산구효자동2가12611220211746200N
25185완산구중화산동2가569420211583000N
95673덕진구산정동858120211734000N
47863완산구삼천동2가69412021198700N
시군구읍면동본번부번기준년도기준월공시지가표준지여부
54778완산구효자동1가630120211456800N
56047완산구효자동2가857220211188100N
65635완산구색장동858152021146400N
72977덕진구인후동1가5032021113500N
34771완산구평화동1가735220211821100N
70939덕진구진북동8347320211426400N
78296덕진구인후동1가941620211478900N
42221완산구용복동201420211124500N
67745완산구서노송동6241920211349100N
60097완산구효자동3가1590920211630400N