Overview

Dataset statistics

Number of variables18
Number of observations30
Missing cells29
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory156.4 B

Variable types

Categorical14
Numeric3
Text1

Dataset

Description샘플 데이터
Author한국평가데이터㈜
URLhttps://www.bigdata-region.kr/#/dataset/af693047-108b-41fd-b895-771e032f5913

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
지하여부 has constant value ""Constant
비고 has constant value ""Constant
수정일시분초 has constant value ""Constant
작업자명 has constant value ""Constant
신우편번호 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
법정동명 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
우편번호순번 is highly overall correlated with A건물번호 and 10 other fieldsHigh correlation
법정동코드 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
도로명코드 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
기타주소명 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
영문도로명주소 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
구우편번호 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
도로명 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
A건물번호 is highly overall correlated with 건물관리번호 and 9 other fieldsHigh correlation
B건물번호 is highly overall correlated with 우편번호순번High correlation
건물관리번호 is highly overall correlated with A건물번호 and 9 other fieldsHigh correlation
우편번호순번 is highly imbalanced (64.7%)Imbalance
신우편번호 is highly imbalanced (64.7%)Imbalance
기타주소명 is highly imbalanced (64.7%)Imbalance
도로명코드 is highly imbalanced (64.7%)Imbalance
도로명 is highly imbalanced (64.7%)Imbalance
영문도로명주소 is highly imbalanced (64.7%)Imbalance
구우편번호 is highly imbalanced (64.7%)Imbalance
비고 has 29 (96.7%) missing valuesMissing
B건물번호 has 16 (53.3%) zerosZeros

Reproduction

Analysis started2023-12-10 14:03:43.099930
Analysis finished2023-12-10 14:03:47.479275
Duration4.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

우편번호순번
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
4.8890334804002e+24
28 
4.8890334804303e+24
 
2

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4.8890334804002e+24
2nd row4.8890334804002e+24
3rd row4.8890334804002e+24
4th row4.8890334804002e+24
5th row4.8890334804002e+24

Common Values

ValueCountFrequency (%)
4.8890334804002e+24 28
93.3%
4.8890334804303e+24 2
 
6.7%

Length

2023-12-10T23:03:47.646615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:47.864338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4.8890334804002e+24 28
93.3%
4.8890334804303e+24 2
 
6.7%

신우편번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
50213
28 
50239
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50213
2nd row50213
3rd row50213
4th row50213
5th row50213

Common Values

ValueCountFrequency (%)
50213 28
93.3%
50239 2
 
6.7%

Length

2023-12-10T23:03:48.036378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:48.186680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50213 28
93.3%
50239 2
 
6.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
경남
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경남 30
100.0%

Length

2023-12-10T23:03:48.349345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:48.494023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경남 30
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
합천군
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합천군 30
100.0%

Length

2023-12-10T23:03:48.666453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:48.843407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합천군 30
100.0%

기타주소명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
용주면
28 
대양면
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용주면 28
93.3%
대양면 2
 
6.7%

Length

2023-12-10T23:03:49.028492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:49.183004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용주면 28
93.3%
대양면 2
 
6.7%

도로명코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
488903348040
28 
488903348043
 
2

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row488903348040
2nd row488903348040
3rd row488903348040
4th row488903348040
5th row488903348040

Common Values

ValueCountFrequency (%)
488903348040 28
93.3%
488903348043 2
 
6.7%

Length

2023-12-10T23:03:49.402727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:49.590424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
488903348040 28
93.3%
488903348043 2
 
6.7%

도로명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
황계폭포로
28 
대야로
 
2

Length

Max length5
Median length5
Mean length4.8666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
황계폭포로 28
93.3%
대야로 2
 
6.7%

Length

2023-12-10T23:03:49.939803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:50.154479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
황계폭포로 28
93.3%
대야로 2
 
6.7%

지하여부
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2023-12-10T23:03:50.387171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:51.217426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

A건물번호
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1401.2333
Minimum675
Maximum1612
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:51.421072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum675
5-th percentile994.5
Q11394.25
median1398
Q31480
95-th percentile1600.2
Maximum1612
Range937
Interquartile range (IQR)85.75

Descriptive statistics

Standard deviation213.33601
Coefficient of variation (CV)0.15224874
Kurtosis8.2442975
Mean1401.2333
Median Absolute Deviation (MAD)13
Skewness-2.7304685
Sum42037
Variance45512.254
MonotonicityNot monotonic
2023-12-10T23:03:51.669613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1398 6
20.0%
1385 4
 
13.3%
675 2
 
6.7%
1490 1
 
3.3%
1612 1
 
3.3%
1602 1
 
3.3%
1598 1
 
3.3%
1596 1
 
3.3%
1586 1
 
3.3%
1569 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
675 2
 
6.7%
1385 4
13.3%
1392 1
 
3.3%
1394 1
 
3.3%
1395 1
 
3.3%
1396 1
 
3.3%
1397 1
 
3.3%
1398 6
20.0%
1406 1
 
3.3%
1424 1
 
3.3%
ValueCountFrequency (%)
1612 1
3.3%
1602 1
3.3%
1598 1
3.3%
1596 1
3.3%
1586 1
3.3%
1569 1
3.3%
1560 1
3.3%
1490 1
3.3%
1450 1
3.3%
1448 1
3.3%

B건물번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8333333
Minimum0
Maximum95
Zeros16
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:51.905039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36.75
95-th percentile12.75
Maximum95
Range95
Interquartile range (IQR)6.75

Descriptive statistics

Standard deviation17.316692
Coefficient of variation (CV)2.9685757
Kurtosis26.496066
Mean5.8333333
Median Absolute Deviation (MAD)0
Skewness5.025495
Sum175
Variance299.86782
MonotonicityNot monotonic
2023-12-10T23:03:52.142163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 16
53.3%
3 2
 
6.7%
7 2
 
6.7%
8 2
 
6.7%
1 2
 
6.7%
2 1
 
3.3%
10 1
 
3.3%
6 1
 
3.3%
9 1
 
3.3%
15 1
 
3.3%
ValueCountFrequency (%)
0 16
53.3%
1 2
 
6.7%
2 1
 
3.3%
3 2
 
6.7%
6 1
 
3.3%
7 2
 
6.7%
8 2
 
6.7%
9 1
 
3.3%
10 1
 
3.3%
15 1
 
3.3%
ValueCountFrequency (%)
95 1
3.3%
15 1
3.3%
10 1
3.3%
9 1
3.3%
8 2
6.7%
7 2
6.7%
6 1
3.3%
3 2
6.7%
2 1
3.3%
1 2
6.7%

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing29
Missing (%)96.7%
Memory size372.0 B
2023-12-10T23:03:52.400016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
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

Unique1 ?
Unique (%)100.0%

Sample

1st row손목경로당
ValueCountFrequency (%)
손목경로당 1
100.0%
2023-12-10T23:03:52.928855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
손 1
20.0%
목 1
20.0%
경 1
20.0%
로 1
20.0%
당 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
손 1
20.0%
목 1
20.0%
경 1
20.0%
로 1
20.0%
당 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
손 1
20.0%
목 1
20.0%
경 1
20.0%
로 1
20.0%
당 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
손 1
20.0%
목 1
20.0%
경 1
20.0%
로 1
20.0%
당 1
20.0%

법정동코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
4889046026
20 
4889046029
8 
4889041021
 
2

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4889046026
2nd row4889046026
3rd row4889046026
4th row4889046026
5th row4889046026

Common Values

ValueCountFrequency (%)
4889046026 20
66.7%
4889046029 8
 
26.7%
4889041021 2
 
6.7%

Length

2023-12-10T23:03:53.228400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:53.393775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4889046026 20
66.7%
4889046029 8
 
26.7%
4889041021 2
 
6.7%

법정동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
손목리
20 
성산리
8 
정양리
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
손목리 20
66.7%
성산리 8
 
26.7%
정양리 2
 
6.7%

Length

2023-12-10T23:03:53.560313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:53.742262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
손목리 20
66.7%
성산리 8
 
26.7%
정양리 2
 
6.7%

건물관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8890457 × 1024
Minimum4.889041 × 1024
Maximum4.889046 × 1024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:54.008023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.889041 × 1024
5-th percentile4.8890433 × 1024
Q14.889046 × 1024
median4.889046 × 1024
Q34.889046 × 1024
95-th percentile4.889046 × 1024
Maximum4.889046 × 1024
Range5.0080988 × 1018
Interquartile range (IQR)2.2498606 × 1015

Descriptive statistics

Standard deviation1.2700291 × 1018
Coefficient of variation (CV)2.5977034 × 10-7
Kurtosis12.206598
Mean4.8890457 × 1024
Median Absolute Deviation (MAD)9.948218 × 1011
Skewness-3.6599916
Sum1.4667137 × 1026
Variance1.6129738 × 1036
MonotonicityNot monotonic
2023-12-10T23:03:54.208782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4.88904602610209e+24 3
 
10.0%
4.88904102110198e+24 2
 
6.7%
4.88904602610202e+24 2
 
6.7%
4.8890460261011e+24 2
 
6.7%
4.889046026101031e+24 2
 
6.7%
4.88904602610109e+24 1
 
3.3%
4.8890460292008e+24 1
 
3.3%
4.8890460291005e+24 1
 
3.3%
4.889046029101591e+24 1
 
3.3%
4.88904602910186e+24 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
4.88904102110198e+24 2
6.7%
4.88904602610034e+24 1
3.3%
4.889046026101031e+24 2
6.7%
4.88904602610104e+24 1
3.3%
4.88904602610109e+24 1
3.3%
4.8890460261011e+24 2
6.7%
4.889046026101351e+24 1
3.3%
4.88904602610136e+24 1
3.3%
4.889046026101649e+24 1
3.3%
4.88904602610202e+24 2
6.7%
ValueCountFrequency (%)
4.8890460292008e+24 1
3.3%
4.889046029200369e+24 1
3.3%
4.88904602910186e+24 1
3.3%
4.889046029101591e+24 1
3.3%
4.88904602910154e+24 1
3.3%
4.8890460291015e+24 1
3.3%
4.8890460291014e+24 1
3.3%
4.8890460291005e+24 1
3.3%
4.88904602610234e+24 1
3.3%
4.88904602610216e+24 1
3.3%

수정일시분초
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2019-07-18
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-07-18
2nd row2019-07-18
3rd row2019-07-18
4th row2019-07-18
5th row2019-07-18

Common Values

ValueCountFrequency (%)
2019-07-18 30
100.0%

Length

2023-12-10T23:03:54.421269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:54.632667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-07-18 30
100.0%

작업자명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
20110
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20110
2nd row20110
3rd row20110
4th row20110
5th row20110

Common Values

ValueCountFrequency (%)
20110 30
100.0%

Length

2023-12-10T23:03:54.803203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:54.944277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20110 30
100.0%

영문도로명주소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do
28 
Daeya-ro; Daeyang-myeon; Hapcheon-gun; Gyeongsangnam-do
 
2

Length

Max length62
Median length62
Mean length61.533333
Min length55

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do
2nd rowHwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do
3rd rowHwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do
4th rowHwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do
5th rowHwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do

Common Values

ValueCountFrequency (%)
Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do 28
93.3%
Daeya-ro; Daeyang-myeon; Hapcheon-gun; Gyeongsangnam-do 2
 
6.7%

Length

2023-12-10T23:03:55.178320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:55.381713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hapcheon-gun 30
25.0%
gyeongsangnam-do 30
25.0%
hwanggyepokpo-ro 28
23.3%
yongju-myeon 28
23.3%
daeya-ro 2
 
1.7%
daeyang-myeon 2
 
1.7%

구우편번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
678913
28 
678942
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row678913
2nd row678913
3rd row678913
4th row678913
5th row678913

Common Values

ValueCountFrequency (%)
678913 28
93.3%
678942 2
 
6.7%

Length

2023-12-10T23:03:55.590476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:55.754714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
678913 28
93.3%
678942 2
 
6.7%

Interactions

2023-12-10T23:03:45.662012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:44.458676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:45.088157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:45.921872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:44.607792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:45.212915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:46.166403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:44.752129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:45.330293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:03:55.904679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호순번신우편번호기타주소명도로명코드도로명A건물번호B건물번호법정동코드법정동명건물관리번호영문도로명주소구우편번호
우편번호순번1.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.000
신우편번호1.0001.0000.9060.9060.906NaN0.0001.0001.000NaN0.9060.906
기타주소명1.0000.9061.0000.9060.906NaN0.0001.0001.000NaN0.9060.906
도로명코드1.0000.9060.9061.0000.906NaN0.0001.0001.000NaN0.9060.906
도로명1.0000.9060.9060.9061.000NaN0.0001.0001.000NaN0.9060.906
A건물번호1.000NaNNaNNaNNaN1.0000.6530.6680.668NaNNaNNaN
B건물번호1.0000.0000.0000.0000.0000.6531.0000.0000.000NaN0.0000.000
법정동코드1.0001.0001.0001.0001.0000.6680.0001.0001.000NaN1.0001.000
법정동명1.0001.0001.0001.0001.0000.6680.0001.0001.000NaN1.0001.000
건물관리번호NaNNaNNaNNaNNaNNaNNaNNaNNaN1.000NaNNaN
영문도로명주소1.0000.9060.9060.9060.906NaN0.0001.0001.000NaN1.0000.906
구우편번호1.0000.9060.9060.9060.906NaN0.0001.0001.000NaN0.9061.000
2023-12-10T23:03:56.142442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신우편번호법정동명우편번호순번법정동코드도로명코드기타주소명영문도로명주소구우편번호도로명
신우편번호1.0000.9821.0000.9820.7210.7210.7210.7210.721
법정동명0.9821.0001.0001.0000.9820.9820.9820.9820.982
우편번호순번1.0001.0001.0001.0001.0001.0001.0001.0001.000
법정동코드0.9821.0001.0001.0000.9820.9820.9820.9820.982
도로명코드0.7210.9821.0000.9821.0000.7210.7210.7210.721
기타주소명0.7210.9821.0000.9820.7211.0000.7210.7210.721
영문도로명주소0.7210.9821.0000.9820.7210.7211.0000.7210.721
구우편번호0.7210.9821.0000.9820.7210.7210.7211.0000.721
도로명0.7210.9821.0000.9820.7210.7210.7210.7211.000
2023-12-10T23:03:56.343194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A건물번호B건물번호건물관리번호우편번호순번신우편번호기타주소명도로명코드도로명법정동코드법정동명영문도로명주소구우편번호
A건물번호1.000-0.2120.7561.0000.9640.9640.9640.9640.9450.9450.9640.964
B건물번호-0.2121.000-0.0821.0000.0000.0000.0000.0000.0000.0000.0000.000
건물관리번호0.756-0.0821.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
우편번호순번1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
신우편번호0.9640.0001.0001.0001.0000.7210.7210.7210.9820.9820.7210.721
기타주소명0.9640.0001.0001.0000.7211.0000.7210.7210.9820.9820.7210.721
도로명코드0.9640.0001.0001.0000.7210.7211.0000.7210.9820.9820.7210.721
도로명0.9640.0001.0001.0000.7210.7210.7211.0000.9820.9820.7210.721
법정동코드0.9450.0001.0001.0000.9820.9820.9820.9821.0001.0000.9820.982
법정동명0.9450.0001.0001.0000.9820.9820.9820.9821.0001.0000.9820.982
영문도로명주소0.9640.0001.0001.0000.7210.7210.7210.7210.9820.9821.0000.721
구우편번호0.9640.0001.0001.0000.7210.7210.7210.7210.9820.9820.7211.000

Missing values

2023-12-10T23:03:46.910535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:03:47.294646image/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

우편번호순번신우편번호시도명시군구명기타주소명도로명코드도로명지하여부A건물번호B건물번호비고법정동코드법정동명건물관리번호수정일시분초작업자명영문도로명주소구우편번호
0488903348040020013850000250213경남합천군용주면488903348040황계폭포로013852<NA>4889046026손목리48890460261010900040532762019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
1488903348040020013850000350213경남합천군용주면488903348040황계폭포로013853<NA>4889046026손목리48890460261010300050532912019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
2488903348040020013850000750213경남합천군용주면488903348040황계폭포로013857<NA>4889046026손목리48890460261010300100533142019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
3488903348040020013850000850213경남합천군용주면488903348040황계폭포로013858<NA>4889046026손목리48890460261010400010533442019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
4488903348040020013920000050213경남합천군용주면488903348040황계폭포로013920<NA>4889046026손목리48890460261023400000532592019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
5488903348040020013940000050213경남합천군용주면488903348040황계폭포로013940<NA>4889046026손목리48890460261020200020532542019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
6488903348040020013950000050213경남합천군용주면488903348040황계폭포로013950손목경로당4889046026손목리48890460261011000050532672019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
7488903348040020013960000050213경남합천군용주면488903348040황계폭포로013960<NA>4889046026손목리48890460261020200030532142019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
8488903348040020013970000050213경남합천군용주면488903348040황계폭포로013970<NA>4889046026손목리48890460261011000060532662019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
9488903348040020013980001050213경남합천군용주면488903348040황계폭포로0139810<NA>4889046026손목리48890460261020900030532292019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
우편번호순번신우편번호시도명시군구명기타주소명도로명코드도로명지하여부A건물번호B건물번호비고법정동코드법정동명건물관리번호수정일시분초작업자명영문도로명주소구우편번호
20488903348040020014900009550213경남합천군용주면488903348040황계폭포로0149095<NA>4889046029성산리48890460292008000000481392019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
21488903348040020015600000050213경남합천군용주면488903348040황계폭포로015600<NA>4889046029성산리48890460291014000040585622019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
22488903348040020015690000050213경남합천군용주면488903348040황계폭포로015690<NA>4889046029성산리48890460291015000000585652019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
23488903348040020015860000050213경남합천군용주면488903348040황계폭포로015860<NA>4889046029성산리48890460291015400000585692019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
24488903348040020015960000050213경남합천군용주면488903348040황계폭포로015960<NA>4889046029성산리48890460292003700010585762019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
25488903348040020015980000050213경남합천군용주면488903348040황계폭포로015980<NA>4889046029성산리48890460291018600070585812019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
26488903348040020016020000050213경남합천군용주면488903348040황계폭포로016020<NA>4889046029성산리48890460291015900000585912019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
27488903348040020016120000150213경남합천군용주면488903348040황계폭포로016121<NA>4889046029성산리48890460291005000010586022019-07-1820110Hwanggyepokpo-ro; Yongju-myeon; Hapcheon-gun; Gyeongsangnam-do678913
28488903348043030006750000050239경남합천군대양면488903348043대야로06750<NA>4889041021정양리48890410211019800010271782019-07-1820110Daeya-ro; Daeyang-myeon; Hapcheon-gun; Gyeongsangnam-do678942
29488903348043030006750000150239경남합천군대양면488903348043대야로06751<NA>4889041021정양리48890410211019800010271752019-07-1820110Daeya-ro; Daeyang-myeon; Hapcheon-gun; Gyeongsangnam-do678942