Overview

Dataset statistics

Number of variables8
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory69.9 B

Variable types

Text4
Categorical1
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
지방청명 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
경찰서명 has unique valuesUnique
소재지우편번호 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:20:08.667613
Analysis finished2023-12-10 21:20:10.199599
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct31
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:20:10.325340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1086957
Min length3

Characters and Unicode

Total characters143
Distinct characters38
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

Unique21 ?
Unique (%)45.7%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row과천시
ValueCountFrequency (%)
수원시 4
 
8.7%
부천시 3
 
6.5%
성남시 3
 
6.5%
고양시 3
 
6.5%
화성시 2
 
4.3%
안양시 2
 
4.3%
안산시 2
 
4.3%
용인시 2
 
4.3%
의정부시 2
 
4.3%
남양주시 2
 
4.3%
Other values (21) 21
45.7%
2023-12-11T06:20:10.655123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 44
30.8%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
성 6
 
4.2%
남 6
 
4.2%
부 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
Other values (28) 46
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
30.8%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
성 6
 
4.2%
남 6
 
4.2%
부 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
Other values (28) 46
32.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 143
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
30.8%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
성 6
 
4.2%
남 6
 
4.2%
부 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
Other values (28) 46
32.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 143
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 44
30.8%
양 9
 
6.3%
천 8
 
5.6%
주 6
 
4.2%
성 6
 
4.2%
남 6
 
4.2%
부 5
 
3.5%
안 5
 
3.5%
수 4
 
2.8%
원 4
 
2.8%
Other values (28) 46
32.2%

지방청명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
경기남부
32 
경기북부
14 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기북부
2nd row경기북부
3rd row경기북부
4th row경기북부
5th row경기남부

Common Values

ValueCountFrequency (%)
경기남부 32
69.6%
경기북부 14
30.4%

Length

2023-12-11T06:20:10.782754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:20:10.864206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기남부 32
69.6%
경기북부 14
30.4%

경찰서명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:20:11.085586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.0869565
Min length5

Characters and Unicode

Total characters280
Distinct characters57
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

Unique46 ?
Unique (%)100.0%

Sample

1st row가평경찰서
2nd row일산서부경찰서
3rd row일산동부경찰서
4th row고양경찰서
5th row과천경찰서
ValueCountFrequency (%)
가평경찰서 1
 
2.2%
오산경찰서 1
 
2.2%
화성동탄경찰서 1
 
2.2%
안산단원경찰서 1
 
2.2%
안성경찰서 1
 
2.2%
안양동안경찰서 1
 
2.2%
안양만안경찰서 1
 
2.2%
양주경찰서 1
 
2.2%
양평경찰서 1
 
2.2%
여주경찰서 1
 
2.2%
Other values (36) 36
78.3%
2023-12-11T06:20:11.453284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 48
17.1%
서 48
17.1%
찰 46
16.4%
부 16
 
5.7%
천 8
 
2.9%
남 8
 
2.9%
양 7
 
2.5%
안 7
 
2.5%
주 6
 
2.1%
원 6
 
2.1%
Other values (47) 80
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 280
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 48
17.1%
서 48
17.1%
찰 46
16.4%
부 16
 
5.7%
천 8
 
2.9%
남 8
 
2.9%
양 7
 
2.5%
안 7
 
2.5%
주 6
 
2.1%
원 6
 
2.1%
Other values (47) 80
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 280
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 48
17.1%
서 48
17.1%
찰 46
16.4%
부 16
 
5.7%
천 8
 
2.9%
남 8
 
2.9%
양 7
 
2.5%
안 7
 
2.5%
주 6
 
2.1%
원 6
 
2.1%
Other values (47) 80
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 280
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 48
17.1%
서 48
17.1%
찰 46
16.4%
부 16
 
5.7%
천 8
 
2.9%
남 8
 
2.9%
양 7
 
2.5%
안 7
 
2.5%
주 6
 
2.1%
원 6
 
2.1%
Other values (47) 80
28.6%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14026.522
Minimum10090
Maximum18487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:20:11.607279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10090
5-th percentile10398
Q111982.25
median13927.5
Q316182
95-th percentile18085
Maximum18487
Range8397
Interquartile range (IQR)4199.75

Descriptive statistics

Standard deviation2483.2217
Coefficient of variation (CV)0.1770376
Kurtosis-1.1478202
Mean14026.522
Median Absolute Deviation (MAD)2155.5
Skewness0.17879196
Sum645220
Variance6166390
MonotonicityNot monotonic
2023-12-11T06:20:11.727684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
12420 1
 
2.2%
17019 1
 
2.2%
17595 1
 
2.2%
14048 1
 
2.2%
14091 1
 
2.2%
11435 1
 
2.2%
12555 1
 
2.2%
12627 1
 
2.2%
11014 1
 
2.2%
18148 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
10090 1
2.2%
10226 1
2.2%
10363 1
2.2%
10503 1
2.2%
10934 1
2.2%
11014 1
2.2%
11153 1
2.2%
11336 1
2.2%
11435 1
2.2%
11664 1
2.2%
ValueCountFrequency (%)
18487 1
2.2%
18277 1
2.2%
18148 1
2.2%
17896 1
2.2%
17595 1
2.2%
17379 1
2.2%
17019 1
2.2%
16905 1
2.2%
16626 1
2.2%
16528 1
2.2%

소재지지번주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:20:12.013032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.173913
Min length16

Characters and Unicode

Total characters928
Distinct characters107
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

Unique46 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 대곡리 229-1번지
2nd row경기도 고양시 일산서구 대화동 2325-1번지
3rd row경기도 고양시 일산동구 정발산동 725번지
4th row경기도 고양시 덕양구 화정동 1008번지
5th row경기도 과천시 중앙동 39번지
ValueCountFrequency (%)
경기도 46
 
22.3%
수원시 4
 
1.9%
성남시 3
 
1.5%
부천시 3
 
1.5%
고양시 3
 
1.5%
정자동 2
 
1.0%
안산시 2
 
1.0%
안양시 2
 
1.0%
1105번지 2
 
1.0%
용인시 2
 
1.0%
Other values (133) 137
66.5%
2023-12-11T06:20:12.457335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
17.2%
기 49
 
5.3%
도 47
 
5.1%
경 46
 
5.0%
지 46
 
5.0%
번 46
 
5.0%
시 44
 
4.7%
동 43
 
4.6%
1 30
 
3.2%
- 22
 
2.4%
Other values (97) 395
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
62.5%
Decimal Number 166
 
17.9%
Space Separator 160
 
17.2%
Dash Punctuation 22
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 49
 
8.4%
도 47
 
8.1%
경 46
 
7.9%
지 46
 
7.9%
번 46
 
7.9%
시 44
 
7.6%
동 43
 
7.4%
구 18
 
3.1%
양 14
 
2.4%
산 13
 
2.2%
Other values (85) 214
36.9%
Decimal Number
ValueCountFrequency (%)
1 30
18.1%
2 20
12.0%
4 18
10.8%
8 17
10.2%
5 17
10.2%
0 16
9.6%
3 14
8.4%
6 14
8.4%
9 11
 
6.6%
7 9
 
5.4%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
62.5%
Common 348
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 49
 
8.4%
도 47
 
8.1%
경 46
 
7.9%
지 46
 
7.9%
번 46
 
7.9%
시 44
 
7.6%
동 43
 
7.4%
구 18
 
3.1%
양 14
 
2.4%
산 13
 
2.2%
Other values (85) 214
36.9%
Common
ValueCountFrequency (%)
160
46.0%
1 30
 
8.6%
- 22
 
6.3%
2 20
 
5.7%
4 18
 
5.2%
8 17
 
4.9%
5 17
 
4.9%
0 16
 
4.6%
3 14
 
4.0%
6 14
 
4.0%
Other values (2) 20
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
62.5%
ASCII 348
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
46.0%
1 30
 
8.6%
- 22
 
6.3%
2 20
 
5.7%
4 18
 
5.2%
8 17
 
4.9%
5 17
 
4.9%
0 16
 
4.6%
3 14
 
4.0%
6 14
 
4.0%
Other values (2) 20
 
5.7%
Hangul
ValueCountFrequency (%)
기 49
 
8.4%
도 47
 
8.1%
경 46
 
7.9%
지 46
 
7.9%
번 46
 
7.9%
시 44
 
7.6%
동 43
 
7.4%
구 18
 
3.1%
양 14
 
2.4%
산 13
 
2.2%
Other values (85) 214
36.9%

소재지도로명주소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T06:20:12.785420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length18.086957
Min length14

Characters and Unicode

Total characters832
Distinct characters123
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

Unique46 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 가화로 61
2nd row경기도 고양시 일산서구 중앙로 1640
3rd row경기도 고양시 일산동구 중앙로 1338
4th row경기도 고양시 덕양구 화중로 12
5th row경기도 과천시 통영로 20
ValueCountFrequency (%)
경기도 46
 
22.3%
수원시 4
 
1.9%
부천시 3
 
1.5%
성남시 3
 
1.5%
중앙로 3
 
1.5%
고양시 3
 
1.5%
140 2
 
1.0%
32 2
 
1.0%
안산시 2
 
1.0%
70 2
 
1.0%
Other values (128) 136
66.0%
2023-12-11T06:20:13.214732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
19.2%
경 48
 
5.8%
기 48
 
5.8%
도 46
 
5.5%
시 45
 
5.4%
로 45
 
5.4%
1 27
 
3.2%
3 21
 
2.5%
2 19
 
2.3%
구 18
 
2.2%
Other values (113) 355
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 523
62.9%
Space Separator 160
 
19.2%
Decimal Number 148
 
17.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 48
 
9.2%
기 48
 
9.2%
도 46
 
8.8%
시 45
 
8.6%
로 45
 
8.6%
구 18
 
3.4%
양 14
 
2.7%
천 12
 
2.3%
남 10
 
1.9%
길 10
 
1.9%
Other values (101) 227
43.4%
Decimal Number
ValueCountFrequency (%)
1 27
18.2%
3 21
14.2%
2 19
12.8%
5 16
10.8%
6 15
10.1%
9 15
10.1%
0 13
8.8%
4 10
 
6.8%
7 9
 
6.1%
8 3
 
2.0%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 523
62.9%
Common 309
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 48
 
9.2%
기 48
 
9.2%
도 46
 
8.8%
시 45
 
8.6%
로 45
 
8.6%
구 18
 
3.4%
양 14
 
2.7%
천 12
 
2.3%
남 10
 
1.9%
길 10
 
1.9%
Other values (101) 227
43.4%
Common
ValueCountFrequency (%)
160
51.8%
1 27
 
8.7%
3 21
 
6.8%
2 19
 
6.1%
5 16
 
5.2%
6 15
 
4.9%
9 15
 
4.9%
0 13
 
4.2%
4 10
 
3.2%
7 9
 
2.9%
Other values (2) 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 523
62.9%
ASCII 309
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
51.8%
1 27
 
8.7%
3 21
 
6.8%
2 19
 
6.1%
5 16
 
5.2%
6 15
 
4.9%
9 15
 
4.9%
0 13
 
4.2%
4 10
 
3.2%
7 9
 
2.9%
Other values (2) 4
 
1.3%
Hangul
ValueCountFrequency (%)
경 48
 
9.2%
기 48
 
9.2%
도 46
 
8.8%
시 45
 
8.6%
로 45
 
8.6%
구 18
 
3.4%
양 14
 
2.7%
천 12
 
2.3%
남 10
 
1.9%
길 10
 
1.9%
Other values (101) 227
43.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.471112
Minimum36.994866
Maximum38.098287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:20:13.371037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.994866
5-th percentile37.16158
Q137.298105
median37.435831
Q337.63534
95-th percentile37.880519
Maximum38.098287
Range1.1034206
Interquartile range (IQR)0.33723519

Descriptive statistics

Standard deviation0.24116461
Coefficient of variation (CV)0.0064360143
Kurtosis-0.039776347
Mean37.471112
Median Absolute Deviation (MAD)0.15702489
Skewness0.41295411
Sum1723.6712
Variance0.05816037
MonotonicityNot monotonic
2023-12-11T06:20:13.502620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
37.8255337017 1
 
2.2%
37.2415620313 1
 
2.2%
37.0004900988 1
 
2.2%
37.3912507706 1
 
2.2%
37.3873381265 1
 
2.2%
37.840809067 1
 
2.2%
37.4884861857 1
 
2.2%
37.2932054298 1
 
2.2%
38.0982867177 1
 
2.2%
37.1536305849 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
36.9948660902 1
2.2%
37.0004900988 1
2.2%
37.1536305849 1
2.2%
37.1854269136 1
2.2%
37.1913091343 1
2.2%
37.2415620313 1
2.2%
37.2587369985 1
2.2%
37.2721182151 1
2.2%
37.2735965166 1
2.2%
37.2932054298 1
2.2%
ValueCountFrequency (%)
38.0982867177 1
2.2%
37.9101585423 1
2.2%
37.8937555812 1
2.2%
37.840809067 1
2.2%
37.8255337017 1
2.2%
37.7574315212 1
2.2%
37.7537188671 1
2.2%
37.7445620554 1
2.2%
37.7099839662 1
2.2%
37.6799943538 1
2.2%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0403
Minimum126.68107
Maximum127.63552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T06:20:13.632211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68107
5-th percentile126.77025
Q1126.85034
median127.05041
Q3127.15988
95-th percentile127.47631
Maximum127.63552
Range0.95445555
Interquartile range (IQR)0.30953935

Descriptive statistics

Standard deviation0.21414447
Coefficient of variation (CV)0.0016856421
Kurtosis0.52596581
Mean127.0403
Median Absolute Deviation (MAD)0.12722439
Skewness0.67775282
Sum5843.8536
Variance0.045857854
MonotonicityNot monotonic
2023-12-11T06:20:13.776262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
127.5150219187 1
 
2.2%
127.1804291184 1
 
2.2%
127.2496953806 1
 
2.2%
126.9488607825 1
 
2.2%
126.9259803406 1
 
2.2%
127.054900181 1
 
2.2%
127.4901474957 1
 
2.2%
127.6355247485 1
 
2.2%
127.0737237027 1
 
2.2%
127.0822266731 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
126.6810691981 1
2.2%
126.7405146327 1
2.2%
126.769534608 1
2.2%
126.772398592 1
2.2%
126.7773322693 1
2.2%
126.7787890024 1
2.2%
126.7881062989 1
2.2%
126.8002882541 1
2.2%
126.8227288101 1
2.2%
126.8295603289 1
2.2%
ValueCountFrequency (%)
127.6355247485 1
2.2%
127.5150219187 1
2.2%
127.4901474957 1
2.2%
127.4347931289 1
2.2%
127.2496953806 1
2.2%
127.2394842428 1
2.2%
127.2246485753 1
2.2%
127.2053021333 1
2.2%
127.1836584828 1
2.2%
127.1804291184 1
2.2%

Interactions

2023-12-11T06:20:09.784006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.040066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.552691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.856019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.112304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.626378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.939275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.198146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:20:09.707738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:20:13.887141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명지방청명경찰서명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0000.9991.0001.0000.9850.964
지방청명1.0001.0001.0000.9961.0001.0000.9970.000
경찰서명1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9990.9961.0001.0001.0001.0000.8670.729
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9850.9971.0000.8671.0001.0001.0000.000
WGS84경도0.9640.0001.0000.7291.0001.0000.0001.000
2023-12-11T06:20:14.035002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도지방청명
소재지우편번호1.000-0.9040.0840.810
WGS84위도-0.9041.000-0.1050.860
WGS84경도0.084-0.1051.0000.000
지방청명0.8100.8600.0001.000

Missing values

2023-12-11T06:20:10.039576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:20:10.152548image/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

시군명지방청명경찰서명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군경기북부가평경찰서12420경기도 가평군 가평읍 대곡리 229-1번지경기도 가평군 가평읍 가화로 6137.825534127.515022
1고양시경기북부일산서부경찰서10226경기도 고양시 일산서구 대화동 2325-1번지경기도 고양시 일산서구 중앙로 164037.679994126.740515
2고양시경기북부일산동부경찰서10363경기도 고양시 일산동구 정발산동 725번지경기도 고양시 일산동구 중앙로 133837.664999126.769535
3고양시경기북부고양경찰서10503경기도 고양시 덕양구 화정동 1008번지경기도 고양시 덕양구 화중로 1237.628709126.829818
4과천시경기남부과천경찰서13807경기도 과천시 중앙동 39번지경기도 과천시 통영로 2037.429356126.989972
5광명시경기남부광명경찰서14240경기도 광명시 철산동 418번지경기도 광명시 디지털로 537.474153126.868578
6광주시경기남부광주경찰서12749경기도 광주시 탄벌동 541-2번지경기도 광주시 포돌이로 13537.408825127.239484
7구리시경기북부구리경찰서11954경기도 구리시 교문동 462-3번지경기도 구리시 아차산로 35937.587646127.128416
8군포시경기남부군포경찰서15829경기도 군포시 금정동 848번지경기도 군포시 산본로324번길 1637.360526126.936088
9김포시경기남부김포경찰서10090경기도 김포시 장기동 2083-7번지경기도 김포시 태장로795번길 6537.63755126.681069
시군명지방청명경찰서명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
36의왕시경기남부의왕경찰서16074경기도 의왕시 고천동 328-10번지경기도 의왕시 시청로 9637.350678126.96816
37의정부시경기북부의정부경찰서11664경기도 의정부시 의정부동 420번지경기도 의정부시 호국로 126537.744562127.044263
38의정부시경기북부경기도북부경찰청11763경기도 의정부시 금오동 481번지경기도 의정부시 금오로23번길 22-4937.757432127.070283
39이천시경기남부이천경찰서17379경기도 이천시 중리동 350-1번지경기도 이천시 부악로 3237.273597127.434793
40파주시경기북부파주경찰서10934경기도 파주시 금릉동 427번지경기도 파주시 쇠재로 14037.753719126.778789
41평택시경기남부평택경찰서17896경기도 평택시 비전동 619-2번지경기도 평택시 중앙로 6736.994866127.090997
42포천시경기북부포천경찰서11153경기도 포천시 군내면 구읍리 729번지경기도 포천시 군내면 호국로 157037.893756127.205302
43하남시경기남부하남경찰서13024경기도 하남시 하산곡동 594번지경기도 하남시 검단로 2737.52267127.224649
44화성시경기남부화성동탄경찰서18487경기도 화성시 오산동 962-1번지경기도 화성시 동탄대로13길 7037.185427127.093622
45화성시경기남부화성서부경찰서18277경기도 화성시 남양읍 신남리 76-1번지경기도 화성시 남양읍 남양로 57037.191309126.822729