Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory61.3 B

Variable types

Numeric4
Categorical2
Text1

Alerts

지점 has constant value ""Constant
주소 has constant value ""Constant
기본키 is highly overall correlated with 전년대비 증감율(%)High correlation
2019년 개별공시지가 is highly overall correlated with 2020년 개별공시지가High correlation
2020년 개별공시지가 is highly overall correlated with 2019년 개별공시지가High correlation
전년대비 증감율(%) is highly overall correlated with 기본키High correlation
기본키 has unique valuesUnique
지번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:02:59.148972
Analysis finished2023-12-10 13:03:01.527345
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:01.604706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T22:03:01.749610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

지점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-1000-0239S-10
100 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-1000-0239S-10
2nd rowA-1000-0239S-10
3rd rowA-1000-0239S-10
4th rowA-1000-0239S-10
5th rowA-1000-0239S-10

Common Values

ValueCountFrequency (%)
A-1000-0239S-10 100
100.0%

Length

2023-12-10T22:03:01.911945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:02.022342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a-1000-0239s-10 100
100.0%

주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울 강동구 상일동
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울 강동구 상일동
2nd row서울 강동구 상일동
3rd row서울 강동구 상일동
4th row서울 강동구 상일동
5th row서울 강동구 상일동

Common Values

ValueCountFrequency (%)
서울 강동구 상일동 100
100.0%

Length

2023-12-10T22:03:02.141566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:03:02.234921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 100
33.3%
강동구 100
33.3%
상일동 100
33.3%

지번
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:03:02.509048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.55
Min length3

Characters and Unicode

Total characters555
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row[1]
2nd row[2]
3rd row[2-1]
4th row[2-2]
5th row[2-3]
ValueCountFrequency (%)
1 1
 
1.0%
25-1 1
 
1.0%
30-1 1
 
1.0%
30 1
 
1.0%
29-4 1
 
1.0%
29-3 1
 
1.0%
29-2 1
 
1.0%
29-1 1
 
1.0%
28 1
 
1.0%
27 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:03:02.951971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 100
18.0%
] 100
18.0%
- 82
14.8%
2 72
13.0%
1 56
10.1%
3 44
7.9%
4 23
 
4.1%
0 21
 
3.8%
6 15
 
2.7%
5 13
 
2.3%
Other values (3) 29
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 273
49.2%
Open Punctuation 100
 
18.0%
Close Punctuation 100
 
18.0%
Dash Punctuation 82
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 72
26.4%
1 56
20.5%
3 44
16.1%
4 23
 
8.4%
0 21
 
7.7%
6 15
 
5.5%
5 13
 
4.8%
9 12
 
4.4%
8 11
 
4.0%
7 6
 
2.2%
Open Punctuation
ValueCountFrequency (%)
[ 100
100.0%
Close Punctuation
ValueCountFrequency (%)
] 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 555
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
[ 100
18.0%
] 100
18.0%
- 82
14.8%
2 72
13.0%
1 56
10.1%
3 44
7.9%
4 23
 
4.1%
0 21
 
3.8%
6 15
 
2.7%
5 13
 
2.3%
Other values (3) 29
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 100
18.0%
] 100
18.0%
- 82
14.8%
2 72
13.0%
1 56
10.1%
3 44
7.9%
4 23
 
4.1%
0 21
 
3.8%
6 15
 
2.7%
5 13
 
2.3%
Other values (3) 29
 
5.2%

2019년 개별공시지가
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean895085
Minimum184800
Maximum3930000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:03.121291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184800
5-th percentile324700
Q1509000
median521700
Q3868250
95-th percentile2762050
Maximum3930000
Range3745200
Interquartile range (IQR)359250

Descriptive statistics

Standard deviation853133.64
Coefficient of variation (CV)0.95313142
Kurtosis4.677294
Mean895085
Median Absolute Deviation (MAD)49550
Skewness2.2843648
Sum89508500
Variance7.27837 × 1011
MonotonicityNot monotonic
2023-12-10T22:03:03.267021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
509600 14
 
14.0%
324700 9
 
9.0%
521700 9
 
9.0%
893000 3
 
3.0%
508000 3
 
3.0%
509000 3
 
3.0%
534000 3
 
3.0%
471900 2
 
2.0%
184800 2
 
2.0%
536000 2
 
2.0%
Other values (46) 50
50.0%
ValueCountFrequency (%)
184800 2
 
2.0%
203200 1
 
1.0%
324700 9
9.0%
363000 1
 
1.0%
377000 1
 
1.0%
467300 1
 
1.0%
471900 2
 
2.0%
476000 1
 
1.0%
492000 1
 
1.0%
493900 1
 
1.0%
ValueCountFrequency (%)
3930000 1
1.0%
3885000 1
1.0%
3810000 2
2.0%
3276000 1
1.0%
2735000 1
1.0%
2566000 1
1.0%
2530000 1
1.0%
2523000 1
1.0%
2010000 1
1.0%
1866000 1
1.0%

2020년 개별공시지가
Real number (ℝ)

HIGH CORRELATION 

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean964280
Minimum200600
Maximum4190000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:03.409644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200600
5-th percentile349800
Q1535900
median564200
Q3900250
95-th percentile3030000
Maximum4190000
Range3989400
Interquartile range (IQR)364350

Descriptive statistics

Standard deviation919175.85
Coefficient of variation (CV)0.95322505
Kurtosis4.5355787
Mean964280
Median Absolute Deviation (MAD)51350
Skewness2.270026
Sum96428000
Variance8.4488425 × 1011
MonotonicityNot monotonic
2023-12-10T22:03:03.606064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
553200 12
 
12.0%
349800 9
 
9.0%
528600 6
 
6.0%
587000 3
 
3.0%
559000 3
 
3.0%
535000 3
 
3.0%
919000 3
 
3.0%
539500 3
 
3.0%
4070000 2
 
2.0%
200600 2
 
2.0%
Other values (48) 54
54.0%
ValueCountFrequency (%)
200600 2
 
2.0%
211200 1
 
1.0%
349800 9
9.0%
389400 1
 
1.0%
434000 1
 
1.0%
517300 1
 
1.0%
523000 1
 
1.0%
528600 6
6.0%
535000 3
 
3.0%
536200 1
 
1.0%
ValueCountFrequency (%)
4190000 1
1.0%
4150000 1
1.0%
4070000 2
2.0%
3600000 1
1.0%
3000000 1
1.0%
2820000 1
1.0%
2770000 1
1.0%
2760000 1
1.0%
2110000 1
1.0%
2019000 1
1.0%

전년대비 증감율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0789
Minimum1.01
Maximum1.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:03:03.766325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.01
5-th percentile1.01
Q11.07
median1.085
Q31.1
95-th percentile1.15
Maximum1.15
Range0.14
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.033901074
Coefficient of variation (CV)0.031421887
Kurtosis0.077234507
Mean1.0789
Median Absolute Deviation (MAD)0.015
Skewness-0.24163373
Sum107.89
Variance0.0011492828
MonotonicityNot monotonic
2023-12-10T22:03:03.900384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1.09 22
22.0%
1.08 19
19.0%
1.1 16
16.0%
1.03 11
11.0%
1.07 7
 
7.0%
1.01 6
 
6.0%
1.15 6
 
6.0%
1.05 5
 
5.0%
1.11 4
 
4.0%
1.13 2
 
2.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
1.01 6
 
6.0%
1.02 1
 
1.0%
1.03 11
11.0%
1.04 1
 
1.0%
1.05 5
 
5.0%
1.07 7
 
7.0%
1.08 19
19.0%
1.09 22
22.0%
1.1 16
16.0%
1.11 4
 
4.0%
ValueCountFrequency (%)
1.15 6
 
6.0%
1.13 2
 
2.0%
1.11 4
 
4.0%
1.1 16
16.0%
1.09 22
22.0%
1.08 19
19.0%
1.07 7
 
7.0%
1.05 5
 
5.0%
1.04 1
 
1.0%
1.03 11
11.0%

Interactions

2023-12-10T22:03:00.612795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.333057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.707579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.102804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.720957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.431896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.800978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.263503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.832027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.535046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.908566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.411332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.938971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:02:59.618698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.004247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:03:00.522645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:03:03.998595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지번2019년 개별공시지가2020년 개별공시지가전년대비 증감율(%)
기본키1.0001.0000.5230.4840.550
지번1.0001.0001.0001.0001.000
2019년 개별공시지가0.5231.0001.0000.9920.587
2020년 개별공시지가0.4841.0000.9921.0000.687
전년대비 증감율(%)0.5501.0000.5870.6871.000
2023-12-10T22:03:04.114340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키2019년 개별공시지가2020년 개별공시지가전년대비 증감율(%)
기본키1.000-0.214-0.0420.536
2019년 개별공시지가-0.2141.0000.930-0.155
2020년 개별공시지가-0.0420.9301.0000.094
전년대비 증감율(%)0.536-0.1550.0941.000

Missing values

2023-12-10T22:03:01.334774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:03:01.472675image/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

기본키지점주소지번2019년 개별공시지가2020년 개별공시지가전년대비 증감율(%)
01A-1000-0239S-10서울 강동구 상일동[1]173800018810001.08
12A-1000-0239S-10서울 강동구 상일동[2]8440008860001.05
23A-1000-0239S-10서울 강동구 상일동[2-1]186600020190001.08
34A-1000-0239S-10서울 강동구 상일동[2-2]173800018810001.08
45A-1000-0239S-10서울 강동구 상일동[2-3]183000019800001.08
56A-1000-0239S-10서울 강동구 상일동[2-4]5775006534001.13
67A-1000-0239S-10서울 강동구 상일동[2-6]9000009270001.03
78A-1000-0239S-10서울 강동구 상일동[2-7]5775006534001.13
89A-1000-0239S-10서울 강동구 상일동[2-8]8600008860001.03
910A-1000-0239S-10서울 강동구 상일동[3]8160008400001.03
기본키지점주소지번2019년 개별공시지가2020년 개별공시지가전년대비 증감율(%)
9091A-1000-0239S-10서울 강동구 상일동[36-5]8130008940001.1
9192A-1000-0239S-10서울 강동구 상일동[36-6]132000014300001.08
9293A-1000-0239S-10서울 강동구 상일동[37]5180005350001.03
9394A-1000-0239S-10서울 강동구 상일동[38]5180005700001.1
9495A-1000-0239S-10서울 강동구 상일동[39-1]5432006013001.11
9596A-1000-0239S-10서울 강동구 상일동[39-2]5080005590001.1
9697A-1000-0239S-10서울 강동구 상일동[39-3]5096005642001.11
9798A-1000-0239S-10서울 강동구 상일동[39-4]5080005590001.1
9899A-1000-0239S-10서울 강동구 상일동[39-5]5080005590001.1
99100A-1000-0239S-10서울 강동구 상일동[39-7]5490006320001.15