Overview

Dataset statistics

Number of variables10
Number of observations71
Missing cells90
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory84.9 B

Variable types

Categorical3
Text3
DateTime1
Numeric3

Alerts

데이터기준일자 has constant value ""Constant
정제우편번호 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 정제우편번호 and 3 other fieldsHigh correlation
유형 is highly overall correlated with 용도High correlation
용도 is highly overall correlated with 정제WGS84위도 and 2 other fieldsHigh correlation
정제도로명주소 has 35 (49.3%) missing valuesMissing
정제우편번호 has 17 (23.9%) missing valuesMissing
정제WGS84위도 has 19 (26.8%) missing valuesMissing
정제WGS84경도 has 19 (26.8%) missing valuesMissing
명소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:03:50.403648
Analysis finished2023-12-10 23:03:52.395023
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
수원시
20 
파주시
14 
안양시
5 
이천시
5 
남양주시
4 
Other values (16)
23 

Length

Max length4
Median length3
Mean length3.084507
Min length3

Unique

Unique11 ?
Unique (%)15.5%

Sample

1st row수원시
2nd row수원시
3rd row안산시
4th row안성시
5th row안양시

Common Values

ValueCountFrequency (%)
수원시 20
28.2%
파주시 14
19.7%
안양시 5
 
7.0%
이천시 5
 
7.0%
남양주시 4
 
5.6%
화성시 3
 
4.2%
안성시 3
 
4.2%
평택시 2
 
2.8%
하남시 2
 
2.8%
의정부시 2
 
2.8%
Other values (11) 11
15.5%

Length

2023-12-11T08:03:52.457842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 20
28.2%
파주시 14
19.7%
안양시 5
 
7.0%
이천시 5
 
7.0%
남양주시 4
 
5.6%
화성시 3
 
4.2%
안성시 3
 
4.2%
평택시 2
 
2.8%
하남시 2
 
2.8%
의정부시 2
 
2.8%
Other values (11) 11
15.5%

명소명
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T08:03:52.739524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length9.943662
Min length3

Characters and Unicode

Total characters706
Distinct characters178
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row경기도청 구관
2nd row수원시가족여성회관 구)권선구청
3rd row구)안산 대부면사무소
4th row미리내성지 본당
5th row농림축산검역본부
ValueCountFrequency (%)
다리 4
 
3.6%
판문점 4
 
3.6%
가옥 2
 
1.8%
생가 2
 
1.8%
철교 2
 
1.8%
농촌진흥청 2
 
1.8%
수원시가족여성회관 2
 
1.8%
리비교 1
 
0.9%
창전지점 1
 
0.9%
이천농협 1
 
0.9%
Other values (89) 89
80.9%
2023-12-11T08:03:53.214369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
5.5%
구 29
 
4.1%
) 25
 
3.5%
_ 22
 
3.1%
관 16
 
2.3%
경 15
 
2.1%
동 15
 
2.1%
역 13
 
1.8%
교 12
 
1.7%
가 11
 
1.6%
Other values (168) 509
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 600
85.0%
Space Separator 39
 
5.5%
Close Punctuation 25
 
3.5%
Connector Punctuation 22
 
3.1%
Open Punctuation 8
 
1.1%
Uppercase Letter 7
 
1.0%
Decimal Number 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 29
 
4.8%
관 16
 
2.7%
경 15
 
2.5%
동 15
 
2.5%
역 13
 
2.2%
교 12
 
2.0%
가 11
 
1.8%
농 11
 
1.8%
학 10
 
1.7%
서 10
 
1.7%
Other values (156) 458
76.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
Y 1
14.3%
M 1
14.3%
A 1
14.3%
S 1
14.3%
K 1
14.3%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
2 2
40.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 593
84.0%
Common 99
 
14.0%
Latin 7
 
1.0%
Han 7
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 29
 
4.9%
관 16
 
2.7%
경 15
 
2.5%
동 15
 
2.5%
역 13
 
2.2%
교 12
 
2.0%
가 11
 
1.9%
농 11
 
1.9%
학 10
 
1.7%
서 10
 
1.7%
Other values (149) 451
76.1%
Han
ValueCountFrequency (%)
務 1
14.3%
事 1
14.3%
舊 1
14.3%
西 1
14.3%
二 1
14.3%
面 1
14.3%
所 1
14.3%
Common
ValueCountFrequency (%)
39
39.4%
) 25
25.3%
_ 22
22.2%
( 8
 
8.1%
1 3
 
3.0%
2 2
 
2.0%
Latin
ValueCountFrequency (%)
C 2
28.6%
Y 1
14.3%
M 1
14.3%
A 1
14.3%
S 1
14.3%
K 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 593
84.0%
ASCII 106
 
15.0%
CJK 7
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
36.8%
) 25
23.6%
_ 22
20.8%
( 8
 
7.5%
1 3
 
2.8%
2 2
 
1.9%
C 2
 
1.9%
Y 1
 
0.9%
M 1
 
0.9%
A 1
 
0.9%
Other values (2) 2
 
1.9%
Hangul
ValueCountFrequency (%)
구 29
 
4.9%
관 16
 
2.7%
경 15
 
2.5%
동 15
 
2.5%
역 13
 
2.2%
교 12
 
2.0%
가 11
 
1.9%
농 11
 
1.9%
학 10
 
1.7%
서 10
 
1.7%
Other values (149) 451
76.1%
CJK
ValueCountFrequency (%)
務 1
14.3%
事 1
14.3%
舊 1
14.3%
西 1
14.3%
二 1
14.3%
面 1
14.3%
所 1
14.3%

유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
건축물
36 
공간환경
35 

Length

Max length4
Median length3
Mean length3.4929577
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건축물
2nd row건축물
3rd row건축물
4th row공간환경
5th row건축물

Common Values

ValueCountFrequency (%)
건축물 36
50.7%
공간환경 35
49.3%

Length

2023-12-11T08:03:53.389855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:03:53.505126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물 36
50.7%
공간환경 35
49.3%

용도
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
업무시설
13 
교육연구 시설
11 
교량
10 
교정 및 군사시설
5 
종교시설
5 
Other values (18)
27 

Length

Max length11
Median length10
Mean length4.971831
Min length1

Unique

Unique11 ?
Unique (%)15.5%

Sample

1st row업무시설
2nd row업무시설
3rd row업무시설
4th row종교시설
5th row교육연구 시설

Common Values

ValueCountFrequency (%)
업무시설 13
18.3%
교육연구 시설 11
15.5%
교량 10
14.1%
교정 및 군사시설 5
 
7.0%
종교시설 5
 
7.0%
공장 3
 
4.2%
운수시설 3
 
4.2%
단독주택 2
 
2.8%
댐 2
 
2.8%
문화 및 집회시설 2
 
2.8%
Other values (13) 15
21.1%

Length

2023-12-11T08:03:53.606075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 13
12.9%
시설 13
12.9%
교육연구 11
10.9%
교량 10
 
9.9%
및 7
 
6.9%
교정 5
 
5.0%
군사시설 5
 
5.0%
종교시설 5
 
5.0%
공장 3
 
3.0%
운수시설 3
 
3.0%
Other values (18) 26
25.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
Minimum2021-02-19 00:00:00
Maximum2021-02-19 00:00:00
2023-12-11T08:03:53.696450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:53.801551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정제도로명주소
Text

MISSING 

Distinct27
Distinct (%)75.0%
Missing35
Missing (%)49.3%
Memory size700.0 B
2023-12-11T08:03:54.038096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length19.444444
Min length14

Characters and Unicode

Total characters700
Distinct characters95
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)69.4%

Sample

1st row경기도 수원시 팔달구 효원로 1
2nd row경기도 수원시 팔달구 매산로 119
3rd row경기도 안성시 양성면 미리내성지로 416
4th row경기도 안양시 만안구 안양로 175
5th row경기도 의정부시 평화로 564
ValueCountFrequency (%)
경기도 36
20.9%
수원시 16
 
9.3%
권선구 12
 
7.0%
서호로 6
 
3.5%
89 6
 
3.5%
평동로79번길 5
 
2.9%
19 5
 
2.9%
팔달구 3
 
1.7%
파주시 3
 
1.7%
안성시 3
 
1.7%
Other values (68) 77
44.8%
2023-12-11T08:03:54.495368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
19.4%
경 36
 
5.1%
시 36
 
5.1%
기 36
 
5.1%
도 36
 
5.1%
로 32
 
4.6%
9 22
 
3.1%
원 19
 
2.7%
수 18
 
2.6%
1 18
 
2.6%
Other values (85) 311
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 447
63.9%
Space Separator 136
 
19.4%
Decimal Number 112
 
16.0%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 36
 
8.1%
시 36
 
8.1%
기 36
 
8.1%
도 36
 
8.1%
로 32
 
7.2%
원 19
 
4.3%
수 18
 
4.0%
구 18
 
4.0%
길 14
 
3.1%
선 12
 
2.7%
Other values (73) 190
42.5%
Decimal Number
ValueCountFrequency (%)
9 22
19.6%
1 18
16.1%
7 12
10.7%
8 12
10.7%
3 11
9.8%
2 11
9.8%
6 10
8.9%
4 7
 
6.2%
5 7
 
6.2%
0 2
 
1.8%
Space Separator
ValueCountFrequency (%)
136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 447
63.9%
Common 253
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 36
 
8.1%
시 36
 
8.1%
기 36
 
8.1%
도 36
 
8.1%
로 32
 
7.2%
원 19
 
4.3%
수 18
 
4.0%
구 18
 
4.0%
길 14
 
3.1%
선 12
 
2.7%
Other values (73) 190
42.5%
Common
ValueCountFrequency (%)
136
53.8%
9 22
 
8.7%
1 18
 
7.1%
7 12
 
4.7%
8 12
 
4.7%
3 11
 
4.3%
2 11
 
4.3%
6 10
 
4.0%
4 7
 
2.8%
5 7
 
2.8%
Other values (2) 7
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 447
63.9%
ASCII 253
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
53.8%
9 22
 
8.7%
1 18
 
7.1%
7 12
 
4.7%
8 12
 
4.7%
3 11
 
4.3%
2 11
 
4.3%
6 10
 
4.0%
4 7
 
2.8%
5 7
 
2.8%
Other values (2) 7
 
2.8%
Hangul
ValueCountFrequency (%)
경 36
 
8.1%
시 36
 
8.1%
기 36
 
8.1%
도 36
 
8.1%
로 32
 
7.2%
원 19
 
4.3%
수 18
 
4.0%
구 18
 
4.0%
길 14
 
3.1%
선 12
 
2.7%
Other values (73) 190
42.5%

정제지번주소
Text

Distinct59
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-11T08:03:54.820210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length18.71831
Min length11

Characters and Unicode

Total characters1329
Distinct characters109
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)77.5%

Sample

1st row경기도 수원시 팔달구 고등동 42-85
2nd row경기도 수원시 팔달구 교동 74-1
3rd row경기도 안산시 단원구 대부북동 467
4th row경기도 안성시 양성면 미산리 141
5th row경기도 안양시 만안구 안양6동 480
ValueCountFrequency (%)
경기도 71
 
21.3%
수원시 20
 
6.0%
권선구 15
 
4.5%
파주시 14
 
4.2%
서둔동 9
 
2.7%
103-2 6
 
1.8%
평동 6
 
1.8%
이천시 5
 
1.5%
안양시 5
 
1.5%
4-11 5
 
1.5%
Other values (136) 178
53.3%
2023-12-11T08:03:55.293276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
263
19.8%
도 72
 
5.4%
경 71
 
5.3%
기 71
 
5.3%
시 69
 
5.2%
1 53
 
4.0%
동 45
 
3.4%
- 34
 
2.6%
2 33
 
2.5%
구 28
 
2.1%
Other values (99) 590
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 820
61.7%
Space Separator 263
 
19.8%
Decimal Number 212
 
16.0%
Dash Punctuation 34
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 72
 
8.8%
경 71
 
8.7%
기 71
 
8.7%
시 69
 
8.4%
동 45
 
5.5%
구 28
 
3.4%
리 28
 
3.4%
면 25
 
3.0%
수 24
 
2.9%
안 22
 
2.7%
Other values (87) 365
44.5%
Decimal Number
ValueCountFrequency (%)
1 53
25.0%
2 33
15.6%
4 24
11.3%
6 20
 
9.4%
0 19
 
9.0%
3 17
 
8.0%
7 16
 
7.5%
8 13
 
6.1%
5 10
 
4.7%
9 7
 
3.3%
Space Separator
ValueCountFrequency (%)
263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 820
61.7%
Common 509
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 72
 
8.8%
경 71
 
8.7%
기 71
 
8.7%
시 69
 
8.4%
동 45
 
5.5%
구 28
 
3.4%
리 28
 
3.4%
면 25
 
3.0%
수 24
 
2.9%
안 22
 
2.7%
Other values (87) 365
44.5%
Common
ValueCountFrequency (%)
263
51.7%
1 53
 
10.4%
- 34
 
6.7%
2 33
 
6.5%
4 24
 
4.7%
6 20
 
3.9%
0 19
 
3.7%
3 17
 
3.3%
7 16
 
3.1%
8 13
 
2.6%
Other values (2) 17
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 820
61.7%
ASCII 509
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
263
51.7%
1 53
 
10.4%
- 34
 
6.7%
2 33
 
6.5%
4 24
 
4.7%
6 20
 
3.9%
0 19
 
3.7%
3 17
 
3.3%
7 16
 
3.1%
8 13
 
2.6%
Other values (2) 17
 
3.3%
Hangul
ValueCountFrequency (%)
도 72
 
8.8%
경 71
 
8.7%
기 71
 
8.7%
시 69
 
8.4%
동 45
 
5.5%
구 28
 
3.4%
리 28
 
3.4%
면 25
 
3.0%
수 24
 
2.9%
안 22
 
2.7%
Other values (87) 365
44.5%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)74.1%
Missing17
Missing (%)23.9%
Infinite0
Infinite (%)0.0%
Mean14998.556
Minimum10000
Maximum18581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:03:55.470526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10801
Q112347.75
median16436.5
Q316614
95-th percentile18090.2
Maximum18581
Range8581
Interquartile range (IQR)4266.25

Descriptive statistics

Standard deviation2632.5871
Coefficient of variation (CV)0.17552271
Kurtosis-1.2442991
Mean14998.556
Median Absolute Deviation (MAD)1153.5
Skewness-0.55491657
Sum809922
Variance6930515
MonotonicityNot monotonic
2023-12-11T08:03:55.597274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
16614 6
 
8.5%
16600 5
 
7.0%
16463 2
 
2.8%
16429 2
 
2.8%
10808 2
 
2.8%
10801 2
 
2.8%
12283 2
 
2.8%
11674 1
 
1.4%
13992 1
 
1.4%
12542 1
 
1.4%
Other values (30) 30
42.3%
(Missing) 17
23.9%
ValueCountFrequency (%)
10000 1
1.4%
10800 1
1.4%
10801 2
2.8%
10808 2
2.8%
10821 1
1.4%
11014 1
1.4%
11103 1
1.4%
11674 1
1.4%
11692 1
1.4%
12277 1
1.4%
ValueCountFrequency (%)
18581 1
1.4%
18556 1
1.4%
18254 1
1.4%
18002 1
1.4%
17711 1
1.4%
17592 1
1.4%
17588 1
1.4%
17500 1
1.4%
17423 1
1.4%
17369 1
1.4%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)80.8%
Missing19
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean37.399264
Minimum37.006092
Maximum38.101803
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:03:55.717733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.006092
5-th percentile37.051857
Q137.258964
median37.276603
Q337.531536
95-th percentile37.896156
Maximum38.101803
Range1.0957113
Interquartile range (IQR)0.27257287

Descriptive statistics

Standard deviation0.26997888
Coefficient of variation (CV)0.0072188288
Kurtosis-0.067792208
Mean37.399264
Median Absolute Deviation (MAD)0.12681817
Skewness0.90252464
Sum1944.7617
Variance0.072888596
MonotonicityNot monotonic
2023-12-11T08:03:55.858079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
37.2681405706 6
 
8.5%
37.2589635492 5
 
7.0%
37.2748106786 2
 
2.8%
37.2780525388 1
 
1.4%
37.3984933859 1
 
1.4%
37.4104168846 1
 
1.4%
37.4373383627 1
 
1.4%
37.3959747759 1
 
1.4%
37.7397380602 1
 
1.4%
37.2828207603 1
 
1.4%
Other values (32) 32
45.1%
(Missing) 19
26.8%
ValueCountFrequency (%)
37.0060921644 1
1.4%
37.0114021059 1
1.4%
37.0453148155 1
1.4%
37.057209368 1
1.4%
37.104534891 1
1.4%
37.1082823423 1
1.4%
37.1324681824 1
1.4%
37.1448570423 1
1.4%
37.233349146 1
1.4%
37.24376947 1
1.4%
ValueCountFrequency (%)
38.1018034738 1
1.4%
37.9455173207 1
1.4%
37.9031540154 1
1.4%
37.8904296618 1
1.4%
37.8641300323 1
1.4%
37.8584604975 1
1.4%
37.8579660089 1
1.4%
37.7423374605 1
1.4%
37.7397380602 1
1.4%
37.7336183187 1
1.4%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)80.8%
Missing19
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean127.04002
Minimum126.52685
Maximum127.68879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-11T08:03:56.005508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52685
5-th percentile126.69434
Q1126.92688
median126.99316
Q3127.20529
95-th percentile127.45145
Maximum127.68879
Range1.1619492
Interquartile range (IQR)0.27841172

Descriptive statistics

Standard deviation0.24473334
Coefficient of variation (CV)0.0019264271
Kurtosis0.27307778
Mean127.04002
Median Absolute Deviation (MAD)0.094489738
Skewness0.42592977
Sum6606.0811
Variance0.059894407
MonotonicityNot monotonic
2023-12-11T08:03:56.128022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
126.9870801562 6
 
8.5%
126.9931644245 5
 
7.0%
126.9849095752 2
 
2.8%
127.4586256672 1
 
1.4%
126.9233645033 1
 
1.4%
126.912813078 1
 
1.4%
127.6887943233 1
 
1.4%
127.0237413257 1
 
1.4%
127.0414436694 1
 
1.4%
127.4403240907 1
 
1.4%
Other values (32) 32
45.1%
(Missing) 19
26.8%
ValueCountFrequency (%)
126.526845151 1
1.4%
126.5852863736 1
1.4%
126.6911311204 1
1.4%
126.6969667838 1
1.4%
126.7014952729 1
1.4%
126.7021511302 1
1.4%
126.7403709312 1
1.4%
126.7849199709 1
1.4%
126.8256567961 1
1.4%
126.8375120466 1
1.4%
ValueCountFrequency (%)
127.6887943233 1
1.4%
127.5604116819 1
1.4%
127.4586256672 1
1.4%
127.4455715421 1
1.4%
127.4403240907 1
1.4%
127.4152303414 1
1.4%
127.3065893645 1
1.4%
127.2960757306 1
1.4%
127.2811147914 1
1.4%
127.2744676697 1
1.4%

Interactions

2023-12-11T08:03:51.759415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:50.955397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.189166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.858485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.035079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.261810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.936506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.114068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:03:51.659161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:03:56.215593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명명소명유형용도정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
시군명1.0001.0000.5720.9331.0001.0000.9960.9590.949
명소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
유형0.5721.0001.0000.7381.0001.0000.4450.2930.000
용도0.9331.0000.7381.0000.9490.9840.8770.8870.816
정제도로명주소1.0001.0001.0000.9491.0001.0001.0001.0001.000
정제지번주소1.0001.0001.0000.9841.0001.0001.0001.0001.000
정제우편번호0.9961.0000.4450.8771.0001.0001.0000.8800.848
정제WGS84위도0.9591.0000.2930.8871.0001.0000.8801.0000.849
정제WGS84경도0.9491.0000.0000.8161.0001.0000.8480.8491.000
2023-12-11T08:03:56.317400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도유형시군명
용도1.0000.5480.569
유형0.5481.0000.427
시군명0.5690.4271.000
2023-12-11T08:03:56.392444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도시군명유형용도
정제우편번호1.000-0.8820.1490.8790.4330.499
정제WGS84위도-0.8821.000-0.0990.7440.1980.524
정제WGS84경도0.149-0.0991.0000.7120.0000.416
시군명0.8790.7440.7121.0000.4270.569
유형0.4330.1980.0000.4271.0000.548
용도0.4990.5240.4160.5690.5481.000

Missing values

2023-12-11T08:03:52.056978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:03:52.207574image/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.
2023-12-11T08:03:52.328624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명명소명유형용도데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0수원시경기도청 구관건축물업무시설2021-02-19경기도 수원시 팔달구 효원로 1경기도 수원시 팔달구 고등동 42-851644437.275154127.008565
1수원시수원시가족여성회관 구)권선구청건축물업무시설2021-02-19경기도 수원시 팔달구 매산로 119경기도 수원시 팔달구 교동 74-11646337.271767127.013483
2안산시구)안산 대부면사무소건축물업무시설2021-02-19<NA>경기도 안산시 단원구 대부북동 4671564537.243769126.585286
3안성시미리내성지 본당공간환경종교시설2021-02-19경기도 안성시 양성면 미리내성지로 416경기도 안성시 양성면 미산리 1411750037.144857127.259861
4안양시농림축산검역본부건축물교육연구 시설2021-02-19경기도 안양시 만안구 안양로 175경기도 안양시 만안구 안양6동 4801408937.388998126.928046
5안양시안양신필름예술센터(구안양경찰서)건축물문화 및 집회시설2021-02-19<NA>경기도 안양시 만안구 안양6동 576-2<NA><NA><NA>
6연천군연천역 급수탑공간환경급수탑2021-02-19<NA>경기도 연천군 연천읍 차탄리 34-3731101438.101803127.074172
7의정부시전국주한미군한국인노동조합 KSC지부건축물업무시설2021-02-19경기도 의정부시 평화로 564경기도 의정부시 의정부1동 201-121169237.742337127.047035
8파주시임진각_자유의 다리공간환경교량2021-02-19<NA>경기도 파주시 문산읍 마정리 509-110808<NA><NA>
9파주시장단역지_장단역지공간환경교량2021-02-19<NA>경기도 파주시 장단면 동장리 198<NA>37.86413126.702151
시군명명소명유형용도데이터기준일자정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
61하남시제1가나안 농군학교건축물교육연구 시설2021-02-19<NA>경기도 하남시 풍산동 산52-2 외 2<NA><NA><NA>
62화성시수촌교회건축물종교시설2021-02-19경기도 화성시 장안면 수촌큰말길 32경기도 화성시 장안면 수촌리 673 외 4필지1858137.104535126.854114
63화성시정원채 고가건축물전통가옥2021-02-19<NA>경기도 화성시 송림동 681825437.233349126.825657
64수원시구)서울대농업생명과학부_강당공간환경교육연구 시설2021-02-19경기도 수원시 권선구 서호로 89경기도 수원시 권선구 서둔동 103-21661437.268141126.98708
65수원시구)서울대농업생명과학부_수위실공간환경교육연구 시설2021-02-19경기도 수원시 권선구 서호로 89경기도 수원시 권선구 서둔동 103-21661437.268141126.98708
66수원시구)서울대농업생명과학부_본관공간환경교육연구 시설2021-02-19경기도 수원시 권선구 서호로 89경기도 수원시 권선구 서둔동 103-21661437.268141126.98708
67수원시잠사과학박물관건축물문화 및 집회시설2021-02-19<NA>경기도 수원시 권선구 서둔동 61<NA><NA><NA>
68수원시선경직물_공장(2)공간환경공장2021-02-19경기도 수원시 권선구 평동로79번길 19경기도 수원시 권선구 평동 4-111660037.258964126.993164
69수원시선경직물_본관공간환경업무시설2021-02-19경기도 수원시 권선구 평동로79번길 19경기도 수원시 권선구 평동 4-111660037.258964126.993164
70수원시선경직물_사무실공간환경제1종 근린생활 시설2021-02-19경기도 수원시 권선구 평동로79번길 19경기도 수원시 권선구 평동 4-111660037.258964126.993164