Overview

Dataset statistics

Number of variables8
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory74.1 B

Variable types

Numeric4
Categorical3
Text1

Alerts

기준년도 has constant value ""Constant
지점 has constant value ""Constant
주소 has constant value ""Constant
기본키아이디 is highly overall correlated with 전년도개별공시지가(원) and 1 other fieldsHigh correlation
전년도개별공시지가(원) is highly overall correlated with 기본키아이디 and 2 other fieldsHigh correlation
당해년도개별공시지가(원) is highly overall correlated with 전년도개별공시지가(원)High correlation
전년대비변경율((%)) is highly overall correlated with 기본키아이디 and 1 other fieldsHigh correlation
기본키아이디 has unique valuesUnique
지번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 09:56:56.778766
Analysis finished2024-04-21 09:56:59.954301
Duration3.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T18:57:00.060826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2024-04-21T18:57:00.274529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2021
25 

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 25
100.0%

Length

2024-04-21T18:57:00.485589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:57:00.640728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 25
100.0%

지점
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
A-1000-0239S-10
25 

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 25
100.0%

Length

2024-04-21T18:57:00.800219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:57:00.957299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a-1000-0239s-10 25
100.0%

주소
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
서울 강동구 상일동
25 

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 25
100.0%

Length

2024-04-21T18:57:01.118800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:57:01.274629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울 25
33.3%
강동구 25
33.3%
상일동 25
33.3%

지번
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
2024-04-21T18:57:01.869301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.08
Min length3

Characters and Unicode

Total characters127
Distinct characters12
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

Unique25 ?
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
 
4.0%
4-8 1
 
4.0%
10-6 1
 
4.0%
10-5 1
 
4.0%
10-1 1
 
4.0%
8-4 1
 
4.0%
8-2 1
 
4.0%
8-1 1
 
4.0%
4-14 1
 
4.0%
4-13 1
 
4.0%
Other values (15) 15
60.0%
2024-04-21T18:57:02.778361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 25
19.7%
] 25
19.7%
- 22
17.3%
1 15
11.8%
2 12
9.4%
4 12
9.4%
8 5
 
3.9%
3 3
 
2.4%
6 3
 
2.4%
0 3
 
2.4%
Other values (2) 2
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
43.3%
Open Punctuation 25
19.7%
Close Punctuation 25
19.7%
Dash Punctuation 22
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
27.3%
2 12
21.8%
4 12
21.8%
8 5
 
9.1%
3 3
 
5.5%
6 3
 
5.5%
0 3
 
5.5%
7 1
 
1.8%
5 1
 
1.8%
Open Punctuation
ValueCountFrequency (%)
[ 25
100.0%
Close Punctuation
ValueCountFrequency (%)
] 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
[ 25
19.7%
] 25
19.7%
- 22
17.3%
1 15
11.8%
2 12
9.4%
4 12
9.4%
8 5
 
3.9%
3 3
 
2.4%
6 3
 
2.4%
0 3
 
2.4%
Other values (2) 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 25
19.7%
] 25
19.7%
- 22
17.3%
1 15
11.8%
2 12
9.4%
4 12
9.4%
8 5
 
3.9%
3 3
 
2.4%
6 3
 
2.4%
0 3
 
2.4%
Other values (2) 2
 
1.6%

전년도개별공시지가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean978116
Minimum349800
Maximum2019000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T18:57:03.134372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum349800
5-th percentile349800
Q1528600
median886000
Q3927000
95-th percentile1993600
Maximum2019000
Range1669200
Interquartile range (IQR)398400

Descriptive statistics

Standard deviation590378.17
Coefficient of variation (CV)0.60358707
Kurtosis-0.66337162
Mean978116
Median Absolute Deviation (MAD)357400
Skewness0.93748499
Sum24452900
Variance3.4854639 × 1011
MonotonicityNot monotonic
2024-04-21T18:57:03.498219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
528600 4
16.0%
919000 3
12.0%
349800 3
12.0%
1881000 2
8.0%
886000 2
8.0%
653400 2
8.0%
539500 2
8.0%
2019000 1
 
4.0%
1980000 1
 
4.0%
927000 1
 
4.0%
Other values (4) 4
16.0%
ValueCountFrequency (%)
349800 3
12.0%
528600 4
16.0%
539500 2
8.0%
653400 2
8.0%
840000 1
 
4.0%
886000 2
8.0%
889300 1
 
4.0%
919000 3
12.0%
927000 1
 
4.0%
1881000 2
8.0%
ValueCountFrequency (%)
2019000 1
 
4.0%
1997000 1
 
4.0%
1980000 1
 
4.0%
1960000 1
 
4.0%
1881000 2
8.0%
927000 1
 
4.0%
919000 3
12.0%
889300 1
 
4.0%
886000 2
8.0%
840000 1
 
4.0%

당해년도개별공시지가(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean948592
Minimum412500
Maximum2126000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T18:57:03.843270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum412500
5-th percentile412500
Q1587500
median587500
Q31080000
95-th percentile2104400
Maximum2126000
Range1713500
Interquartile range (IQR)492500

Descriptive statistics

Standard deviation654755.49
Coefficient of variation (CV)0.69023931
Kurtosis-0.48474924
Mean948592
Median Absolute Deviation (MAD)53200
Skewness1.1878311
Sum23714800
Variance4.2870475 × 1011
MonotonicityNot monotonic
2024-04-21T18:57:04.212936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
587500 7
28.0%
412500 3
12.0%
1999000 2
 
8.0%
558100 2
 
8.0%
694600 2
 
8.0%
618700 2
 
8.0%
2126000 1
 
4.0%
2105000 1
 
4.0%
593700 1
 
4.0%
534300 1
 
4.0%
Other values (3) 3
12.0%
ValueCountFrequency (%)
412500 3
12.0%
534300 1
 
4.0%
558100 2
 
8.0%
587500 7
28.0%
593700 1
 
4.0%
618700 2
 
8.0%
694600 2
 
8.0%
1080000 1
 
4.0%
1999000 2
 
8.0%
2083000 1
 
4.0%
ValueCountFrequency (%)
2126000 1
 
4.0%
2105000 1
 
4.0%
2102000 1
 
4.0%
2083000 1
 
4.0%
1999000 2
 
8.0%
1080000 1
 
4.0%
694600 2
 
8.0%
618700 2
 
8.0%
593700 1
 
4.0%
587500 7
28.0%

전년대비변경율((%))
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9764
Minimum0.63
Maximum1.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T18:57:04.549442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.63
5-th percentile0.632
Q10.64
median1.06
Q31.11
95-th percentile1.18
Maximum1.21
Range0.58
Interquartile range (IQR)0.47

Descriptive statistics

Standard deviation0.22071626
Coefficient of variation (CV)0.22605106
Kurtosis-1.0603524
Mean0.9764
Median Absolute Deviation (MAD)0.09
Skewness-0.88918435
Sum24.41
Variance0.048715667
MonotonicityNot monotonic
2024-04-21T18:57:04.877160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1.06 6
24.0%
0.64 5
20.0%
1.11 4
16.0%
1.18 3
12.0%
0.63 2
 
8.0%
1.05 2
 
8.0%
1.15 2
 
8.0%
1.21 1
 
4.0%
ValueCountFrequency (%)
0.63 2
 
8.0%
0.64 5
20.0%
1.05 2
 
8.0%
1.06 6
24.0%
1.11 4
16.0%
1.15 2
 
8.0%
1.18 3
12.0%
1.21 1
 
4.0%
ValueCountFrequency (%)
1.21 1
 
4.0%
1.18 3
12.0%
1.15 2
 
8.0%
1.11 4
16.0%
1.06 6
24.0%
1.05 2
 
8.0%
0.64 5
20.0%
0.63 2
 
8.0%

Interactions

2024-04-21T18:56:59.004068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.020138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.591340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:58.406138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:59.145194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.154584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.739180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:58.550606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:59.298001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.301207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.891654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:58.702970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:59.454698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:57.452662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:58.259935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:56:58.856917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T18:57:05.111130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키아이디지번전년도개별공시지가(원)당해년도개별공시지가(원)전년대비변경율((%))
기본키아이디1.0001.0000.3200.6890.526
지번1.0001.0001.0001.0001.000
전년도개별공시지가(원)0.3201.0001.0000.9330.940
당해년도개별공시지가(원)0.6891.0000.9331.0000.969
전년대비변경율((%))0.5261.0000.9400.9691.000
2024-04-21T18:57:05.379776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키아이디전년도개별공시지가(원)당해년도개별공시지가(원)전년대비변경율((%))
기본키아이디1.000-0.572-0.3620.626
전년도개별공시지가(원)-0.5721.0000.742-0.606
당해년도개별공시지가(원)-0.3620.7421.000-0.069
전년대비변경율((%))0.626-0.606-0.0691.000

Missing values

2024-04-21T18:56:59.648115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T18:56:59.867804image/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

기본키아이디기준년도지점주소지번전년도개별공시지가(원)당해년도개별공시지가(원)전년대비변경율((%))
012021A-1000-0239S-10서울 강동구 상일동[1]188100019990001.06
122021A-1000-0239S-10서울 강동구 상일동[2]8860005581000.63
232021A-1000-0239S-10서울 강동구 상일동[2-1]201900021260001.05
342021A-1000-0239S-10서울 강동구 상일동[2-2]188100019990001.06
452021A-1000-0239S-10서울 강동구 상일동[2-3]198000021050001.06
562021A-1000-0239S-10서울 강동구 상일동[2-4]6534006946001.06
672021A-1000-0239S-10서울 강동구 상일동[2-6]9270005937000.64
782021A-1000-0239S-10서울 강동구 상일동[2-7]6534006946001.06
892021A-1000-0239S-10서울 강동구 상일동[2-8]8860005581000.63
9102021A-1000-0239S-10서울 강동구 상일동[3]8400005343000.64
기본키아이디기준년도지점주소지번전년도개별공시지가(원)당해년도개별공시지가(원)전년대비변경율((%))
15162021A-1000-0239S-10서울 강동구 상일동[4-12]5286005875001.11
16172021A-1000-0239S-10서울 강동구 상일동[4-13]9190005875000.64
17182021A-1000-0239S-10서울 강동구 상일동[4-14]9190005875000.64
18192021A-1000-0239S-10서울 강동구 상일동[8-1]3498004125001.18
19202021A-1000-0239S-10서울 강동구 상일동[8-2]3498004125001.18
20212021A-1000-0239S-10서울 강동구 상일동[8-4]3498004125001.18
21222021A-1000-0239S-10서울 강동구 상일동[10-1]5286005875001.11
22232021A-1000-0239S-10서울 강동구 상일동[10-5]88930010800001.21
23242021A-1000-0239S-10서울 강동구 상일동[10-6]5395006187001.15
24252021A-1000-0239S-10서울 강동구 상일동[11-1]5395006187001.15