Overview

Dataset statistics

Number of variables8
Number of observations38
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory70.5 B

Variable types

Text5
Numeric3

Alerts

소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
센터명 has unique valuesUnique

Reproduction

Analysis started2024-03-12 23:15:21.661084
Analysis finished2024-03-12 23:15:22.891367
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct31
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T08:15:22.986742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0789474
Min length3

Characters and Unicode

Total characters117
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

Unique26 ?
Unique (%)68.4%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row과천시
5th row광명시
ValueCountFrequency (%)
수원시 4
 
10.5%
성남시 2
 
5.3%
부천시 2
 
5.3%
화성시 2
 
5.3%
고양시 2
 
5.3%
의정부시 1
 
2.6%
포천시 1
 
2.6%
평택시 1
 
2.6%
파주시 1
 
2.6%
이천시 1
 
2.6%
Other values (21) 21
55.3%
2024-03-13T08:15:23.228534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 36
30.8%
천 7
 
6.0%
양 6
 
5.1%
성 5
 
4.3%
주 5
 
4.3%
수 4
 
3.4%
군 4
 
3.4%
남 4
 
3.4%
원 4
 
3.4%
포 3
 
2.6%
Other values (28) 39
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 36
30.8%
천 7
 
6.0%
양 6
 
5.1%
성 5
 
4.3%
주 5
 
4.3%
수 4
 
3.4%
군 4
 
3.4%
남 4
 
3.4%
원 4
 
3.4%
포 3
 
2.6%
Other values (28) 39
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 36
30.8%
천 7
 
6.0%
양 6
 
5.1%
성 5
 
4.3%
주 5
 
4.3%
수 4
 
3.4%
군 4
 
3.4%
남 4
 
3.4%
원 4
 
3.4%
포 3
 
2.6%
Other values (28) 39
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 36
30.8%
천 7
 
6.0%
양 6
 
5.1%
성 5
 
4.3%
주 5
 
4.3%
수 4
 
3.4%
군 4
 
3.4%
남 4
 
3.4%
원 4
 
3.4%
포 3
 
2.6%
Other values (28) 39
33.3%

센터명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T08:15:23.410675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.815789
Min length11

Characters and Unicode

Total characters449
Distinct characters51
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

Unique38 ?
Unique (%)100.0%

Sample

1st row가평군정신건강복지센터
2nd row고양시아동청소년정신건강복지센터
3rd row고양시정신건강복지센터
4th row과천시정신건강복지센터
5th row광명시정신건강복지센터
ValueCountFrequency (%)
가평군정신건강복지센터 1
 
2.6%
오산시정신건강복지센터 1
 
2.6%
화성시아동청소년정신건강복지센터 1
 
2.6%
안성시정신건강복지센터 1
 
2.6%
안양시정신건강복지센터 1
 
2.6%
양주시정신건강복지센터 1
 
2.6%
양평군정신건강복지센터 1
 
2.6%
여주시정신건강복지센터 1
 
2.6%
연천군정신건강복지센터 1
 
2.6%
의왕시정신건강복지센터 1
 
2.6%
Other values (28) 28
73.7%
2024-03-13T08:15:23.687730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 39
 
8.7%
신 38
 
8.5%
건 38
 
8.5%
강 38
 
8.5%
복 38
 
8.5%
센 38
 
8.5%
터 38
 
8.5%
지 37
 
8.2%
시 35
 
7.8%
천 7
 
1.6%
Other values (41) 103
22.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 449
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 39
 
8.7%
신 38
 
8.5%
건 38
 
8.5%
강 38
 
8.5%
복 38
 
8.5%
센 38
 
8.5%
터 38
 
8.5%
지 37
 
8.2%
시 35
 
7.8%
천 7
 
1.6%
Other values (41) 103
22.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 449
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 39
 
8.7%
신 38
 
8.5%
건 38
 
8.5%
강 38
 
8.5%
복 38
 
8.5%
센 38
 
8.5%
터 38
 
8.5%
지 37
 
8.2%
시 35
 
7.8%
천 7
 
1.6%
Other values (41) 103
22.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 449
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 39
 
8.7%
신 38
 
8.5%
건 38
 
8.5%
강 38
 
8.5%
복 38
 
8.5%
센 38
 
8.5%
터 38
 
8.5%
지 37
 
8.2%
시 35
 
7.8%
천 7
 
1.6%
Other values (41) 103
22.9%

전화번호
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T08:15:23.856084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.973684
Min length11

Characters and Unicode

Total characters455
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)94.7%

Sample

1st row031-581-8881
2nd row031-908-3567
3rd row031-968-2333
4th row02-504-4440
5th row02-897-7786
ValueCountFrequency (%)
032-654-4024 2
 
5.3%
031-581-8881 1
 
2.6%
031-286-0949 1
 
2.6%
031-469-2989 1
 
2.6%
031-840-7320 1
 
2.6%
031-771-3521 1
 
2.6%
031-886-3435 1
 
2.6%
031-832-8106 1
 
2.6%
031-374-8680 1
 
2.6%
031-458-0682 1
 
2.6%
Other values (27) 27
71.1%
2024-03-13T08:15:24.155755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.7%
3 65
14.3%
0 62
13.6%
1 59
13.0%
8 37
8.1%
2 31
6.8%
5 30
 
6.6%
7 30
 
6.6%
6 25
 
5.5%
4 25
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 379
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 65
17.2%
0 62
16.4%
1 59
15.6%
8 37
9.8%
2 31
8.2%
5 30
7.9%
7 30
7.9%
6 25
 
6.6%
4 25
 
6.6%
9 15
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 455
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.7%
3 65
14.3%
0 62
13.6%
1 59
13.0%
8 37
8.1%
2 31
6.8%
5 30
 
6.6%
7 30
 
6.6%
6 25
 
5.5%
4 25
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.7%
3 65
14.3%
0 62
13.6%
1 59
13.0%
8 37
8.1%
2 31
6.8%
5 30
 
6.6%
7 30
 
6.6%
6 25
 
5.5%
4 25
 
5.5%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14128.211
Minimum10111
Maximum18588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-13T08:15:24.263766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10111
5-th percentile10452.5
Q112012.5
median13920.5
Q316403
95-th percentile18156.2
Maximum18588
Range8477
Interquartile range (IQR)4390.5

Descriptive statistics

Standard deviation2564.3706
Coefficient of variation (CV)0.1815071
Kurtosis-1.2409098
Mean14128.211
Median Absolute Deviation (MAD)2321
Skewness0.17080872
Sum536872
Variance6575996.5
MonotonicityNot monotonic
2024-03-13T08:15:24.358172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
13346 2
 
5.3%
12413 1
 
2.6%
16076 1
 
2.6%
11486 1
 
2.6%
12550 1
 
2.6%
12628 1
 
2.6%
11027 1
 
2.6%
18131 1
 
2.6%
16969 1
 
2.6%
11653 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
10111 1
2.6%
10410 1
2.6%
10460 1
2.6%
10937 1
2.6%
11027 1
2.6%
11143 1
2.6%
11344 1
2.6%
11486 1
2.6%
11653 1
2.6%
11922 1
2.6%
ValueCountFrequency (%)
18588 1
2.6%
18299 1
2.6%
18131 1
2.6%
17901 1
2.6%
17596 1
2.6%
17380 1
2.6%
16969 1
2.6%
16703 1
2.6%
16457 1
2.6%
16439 1
2.6%

소재지지번주소
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T08:15:24.561257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21.5
Mean length20.263158
Min length15

Characters and Unicode

Total characters770
Distinct characters99
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

Unique36 ?
Unique (%)94.7%

Sample

1st row경기도 가평군 가평읍 읍내리 624-20번지
2nd row경기도 고양시 일산동구 마두동 1010번지
3rd row경기도 고양시 덕양구 주교동 602-1번지
4th row경기도 과천시 중앙동 1-3번지
5th row경기도 광명시 하안동 230번지
ValueCountFrequency (%)
경기도 38
 
22.2%
수원시 4
 
2.3%
수정구 2
 
1.2%
고양시 2
 
1.2%
성남시 2
 
1.2%
부천시 2
 
1.2%
신흥동 2
 
1.2%
팔달구 2
 
1.2%
화성시 2
 
1.2%
3435번지 2
 
1.2%
Other values (113) 113
66.1%
2024-03-13T08:15:24.874511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
17.3%
도 40
 
5.2%
기 40
 
5.2%
경 39
 
5.1%
번 38
 
4.9%
지 38
 
4.9%
시 36
 
4.7%
동 34
 
4.4%
1 28
 
3.6%
- 20
 
2.6%
Other values (89) 324
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 480
62.3%
Decimal Number 137
 
17.8%
Space Separator 133
 
17.3%
Dash Punctuation 20
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 40
 
8.3%
기 40
 
8.3%
경 39
 
8.1%
번 38
 
7.9%
지 38
 
7.9%
시 36
 
7.5%
동 34
 
7.1%
구 14
 
2.9%
천 9
 
1.9%
양 9
 
1.9%
Other values (77) 183
38.1%
Decimal Number
ValueCountFrequency (%)
1 28
20.4%
3 19
13.9%
8 14
10.2%
6 13
9.5%
5 12
8.8%
4 12
8.8%
0 12
8.8%
7 10
 
7.3%
2 10
 
7.3%
9 7
 
5.1%
Space Separator
ValueCountFrequency (%)
133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 480
62.3%
Common 290
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 40
 
8.3%
기 40
 
8.3%
경 39
 
8.1%
번 38
 
7.9%
지 38
 
7.9%
시 36
 
7.5%
동 34
 
7.1%
구 14
 
2.9%
천 9
 
1.9%
양 9
 
1.9%
Other values (77) 183
38.1%
Common
ValueCountFrequency (%)
133
45.9%
1 28
 
9.7%
- 20
 
6.9%
3 19
 
6.6%
8 14
 
4.8%
6 13
 
4.5%
5 12
 
4.1%
4 12
 
4.1%
0 12
 
4.1%
7 10
 
3.4%
Other values (2) 17
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 480
62.3%
ASCII 290
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
45.9%
1 28
 
9.7%
- 20
 
6.9%
3 19
 
6.6%
8 14
 
4.8%
6 13
 
4.5%
5 12
 
4.1%
4 12
 
4.1%
0 12
 
4.1%
7 10
 
3.4%
Other values (2) 17
 
5.9%
Hangul
ValueCountFrequency (%)
도 40
 
8.3%
기 40
 
8.3%
경 39
 
8.1%
번 38
 
7.9%
지 38
 
7.9%
시 36
 
7.5%
동 34
 
7.1%
구 14
 
2.9%
천 9
 
1.9%
양 9
 
1.9%
Other values (77) 183
38.1%

소재지도로명주소
Text

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
2024-03-13T08:15:25.108714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length17.868421
Min length14

Characters and Unicode

Total characters679
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

Unique36 ?
Unique (%)94.7%

Sample

1st row경기도 가평군 가평읍 가화로 155-15
2nd row경기도 고양시 일산동구 중앙로 1228
3rd row경기도 고양시 덕양구 고양시청로 13-6
4th row경기도 과천시 관문로 69
5th row경기도 광명시 오리로 613
ValueCountFrequency (%)
경기도 38
 
22.5%
수원시 4
 
2.4%
성남시 2
 
1.2%
부천시 2
 
1.2%
고양시 2
 
1.2%
팔달구 2
 
1.2%
화성시 2
 
1.2%
수정구 2
 
1.2%
218 2
 
1.2%
수정로 2
 
1.2%
Other values (111) 111
65.7%
2024-03-13T08:15:25.441787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
19.3%
경 41
 
6.0%
기 41
 
6.0%
로 38
 
5.6%
도 38
 
5.6%
시 37
 
5.4%
1 29
 
4.3%
2 18
 
2.7%
4 13
 
1.9%
5 12
 
1.8%
Other values (97) 281
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 425
62.6%
Space Separator 131
 
19.3%
Decimal Number 120
 
17.7%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 41
 
9.6%
기 41
 
9.6%
로 38
 
8.9%
도 38
 
8.9%
시 37
 
8.7%
구 12
 
2.8%
천 10
 
2.4%
양 9
 
2.1%
수 8
 
1.9%
길 7
 
1.6%
Other values (85) 184
43.3%
Decimal Number
ValueCountFrequency (%)
1 29
24.2%
2 18
15.0%
4 13
10.8%
5 12
10.0%
8 12
10.0%
3 9
 
7.5%
9 8
 
6.7%
6 7
 
5.8%
7 6
 
5.0%
0 6
 
5.0%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 425
62.6%
Common 254
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 41
 
9.6%
기 41
 
9.6%
로 38
 
8.9%
도 38
 
8.9%
시 37
 
8.7%
구 12
 
2.8%
천 10
 
2.4%
양 9
 
2.1%
수 8
 
1.9%
길 7
 
1.6%
Other values (85) 184
43.3%
Common
ValueCountFrequency (%)
131
51.6%
1 29
 
11.4%
2 18
 
7.1%
4 13
 
5.1%
5 12
 
4.7%
8 12
 
4.7%
3 9
 
3.5%
9 8
 
3.1%
6 7
 
2.8%
7 6
 
2.4%
Other values (2) 9
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 425
62.6%
ASCII 254
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
51.6%
1 29
 
11.4%
2 18
 
7.1%
4 13
 
5.1%
5 12
 
4.7%
8 12
 
4.7%
3 9
 
3.5%
9 8
 
3.1%
6 7
 
2.8%
7 6
 
2.4%
Other values (2) 9
 
3.5%
Hangul
ValueCountFrequency (%)
경 41
 
9.6%
기 41
 
9.6%
로 38
 
8.9%
도 38
 
8.9%
시 37
 
8.7%
구 12
 
2.8%
천 10
 
2.4%
양 9
 
2.1%
수 8
 
1.9%
길 7
 
1.6%
Other values (85) 184
43.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.464075
Minimum36.990715
Maximum38.023234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-13T08:15:25.550812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.990715
5-th percentile37.117199
Q137.296699
median37.436772
Q337.632617
95-th percentile37.89714
Maximum38.023234
Range1.0325186
Interquartile range (IQR)0.33591763

Descriptive statistics

Standard deviation0.24567209
Coefficient of variation (CV)0.0065575377
Kurtosis-0.25199842
Mean37.464075
Median Absolute Deviation (MAD)0.16525123
Skewness0.31759659
Sum1423.6349
Variance0.060354774
MonotonicityNot monotonic
2024-03-13T08:15:25.648323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
37.30368069 2
 
5.3%
37.83306369 1
 
2.6%
37.34372723 1
 
2.6%
37.79956067 1
 
2.6%
37.49702065 1
 
2.6%
37.2943722 1
 
2.6%
38.02323386 1
 
2.6%
37.15936559 1
 
2.6%
37.2725816 1
 
2.6%
37.7359883 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
36.99071525 1
2.6%
37.00010628 1
2.6%
37.13786295 1
2.6%
37.15936559 1
2.6%
37.22815347 1
2.6%
37.27032741 1
2.6%
37.27045983 1
2.6%
37.2725816 1
2.6%
37.27931713 1
2.6%
37.2943722 1
2.6%
ValueCountFrequency (%)
38.02323386 1
2.6%
37.90063677 1
2.6%
37.89652313 1
2.6%
37.83306369 1
2.6%
37.79956067 1
2.6%
37.74462142 1
2.6%
37.7359883 1
2.6%
37.65690991 1
2.6%
37.65632859 1
2.6%
37.63566788 1
2.6%

WGS84경도
Real number (ℝ)

Distinct37
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05568
Minimum126.72272
Maximum127.63967
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2024-03-13T08:15:25.742225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72272
5-th percentile126.7747
Q1126.92321
median127.02506
Q3127.14481
95-th percentile127.49022
Maximum127.63967
Range0.9169473
Interquartile range (IQR)0.22159475

Descriptive statistics

Standard deviation0.21842914
Coefficient of variation (CV)0.0017191608
Kurtosis0.50615254
Mean127.05568
Median Absolute Deviation (MAD)0.11948975
Skewness0.78861925
Sum4828.1158
Variance0.047711291
MonotonicityNot monotonic
2024-03-13T08:15:25.837167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
127.0100331 2
 
5.3%
127.5114085 1
 
2.6%
126.9720392 1
 
2.6%
127.1006198 1
 
2.6%
127.4864821 1
 
2.6%
127.6396671 1
 
2.6%
127.0606114 1
 
2.6%
127.0777805 1
 
2.6%
127.106688 1
 
2.6%
127.0395136 1
 
2.6%
Other values (27) 27
71.1%
ValueCountFrequency (%)
126.7227198 1
2.6%
126.7682017 1
2.6%
126.7758474 1
2.6%
126.7809643 1
2.6%
126.784883 1
2.6%
126.8051227 1
2.6%
126.8315185 1
2.6%
126.8320664 1
2.6%
126.8783776 1
2.6%
126.9224111 1
2.6%
ValueCountFrequency (%)
127.6396671 1
2.6%
127.5114085 1
2.6%
127.4864821 1
2.6%
127.4452642 1
2.6%
127.2699333 1
2.6%
127.2502801 1
2.6%
127.2162471 1
2.6%
127.2146137 1
2.6%
127.2011374 1
2.6%
127.1450627 1
2.6%

Interactions

2024-03-13T08:15:22.527730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.168108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.348672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.588299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.224396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.406416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.652358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.283749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:15:22.466238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:15:25.901903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명센터명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0001.0000.9680.988
센터명1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0000.9940.9941.0001.000
소재지우편번호1.0001.0001.0001.0001.0001.0000.8380.710
소재지지번주소1.0001.0000.9941.0001.0001.0001.0001.000
소재지도로명주소1.0001.0000.9941.0001.0001.0001.0001.000
WGS84위도0.9681.0001.0000.8381.0001.0001.0000.000
WGS84경도0.9881.0001.0000.7101.0001.0000.0001.000
2024-03-13T08:15:25.984624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.9090.008
WGS84위도-0.9091.000-0.062
WGS84경도0.008-0.0621.000

Missing values

2024-03-13T08:15:22.737262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:15:22.846038image/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

시군명센터명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
0가평군가평군정신건강복지센터031-581-888112413경기도 가평군 가평읍 읍내리 624-20번지경기도 가평군 가평읍 가화로 155-1537.833064127.511409
1고양시고양시아동청소년정신건강복지센터031-908-356710410경기도 고양시 일산동구 마두동 1010번지경기도 고양시 일산동구 중앙로 122837.656329126.775847
2고양시고양시정신건강복지센터031-968-233310460경기도 고양시 덕양구 주교동 602-1번지경기도 고양시 덕양구 고양시청로 13-637.65691126.832066
3과천시과천시정신건강복지센터02-504-444013806경기도 과천시 중앙동 1-3번지경기도 과천시 관문로 6937.429272126.987449
4광명시광명시정신건강복지센터02-897-778614303경기도 광명시 하안동 230번지경기도 광명시 오리로 61337.455769126.878378
5광주시광주시정신건강복지센터031-762-872812739경기도 광주시 경안동 115번지경기도 광주시 파발로 19437.416364127.25028
6구리시구리시정신건강복지센터031-523-867211922경기도 구리시 인창동 674-3번지경기도 구리시 건원대로34번길 8437.604755127.145063
7군포시군포시정신건강복지센터031-461-177115887경기도 군포시 부곡동 770-1번지경기도 군포시 군포로 22137.332921126.925622
8김포시김포시정신건강복지센터031-998-400510111경기도 김포시 사우동 869번지경기도 김포시 사우중로 10837.623464126.72272
9남양주시남양주시정신건강복지센터031-592-589112284경기도 남양주시 다산동 6198번지경기도 남양주시 경춘로 52237.635668127.216247
시군명센터명전화번호소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
28용인시용인시정신건강복지센터031-286-094916969경기도 용인시 기흥구 신갈동 60-3번지경기도 용인시 기흥구 신갈로58번길 1137.272582127.106688
29의왕시의왕시정신건강복지센터031-458-068216076경기도 의왕시 고천동 108번지경기도 의왕시 오봉로 3437.343727126.972039
30의정부시의정부시정신건강복지센터031-838-418111653경기도 의정부시 의정부동 557-4번지경기도 의정부시 범골로 15837.735988127.039514
31이천시이천시정신건강복지센터031-637-233017380경기도 이천시 증일동 2번지경기도 이천시 이섭대천로 111937.270327127.445264
32파주시파주시정신건강복지센터031-942-211710937경기도 파주시 조리읍 봉일천리 188-9번지경기도 파주시 조리읍 봉천로 6837.744621126.805123
33평택시평택시정신건강복지센터031-658-981817901경기도 평택시 비전동 846번지경기도 평택시 경기대로 24536.990715127.111785
34포천시포천시정신건강복지센터031-532-165511143경기도 포천시 신읍동 164-3번지경기도 포천시 포천로 161237.900637127.201137
35하남시하남시정신건강복지센터031-793-655212909경기도 하남시 망월동 980번지경기도 하남시 미사강변대로 20037.539041127.214614
36화성시화성시아동청소년정신건강복지센터031-305-101018299경기도 화성시 봉담읍 동화리 11-13번지경기도 화성시 봉담읍 효행로 21237.228153126.966407
37화성시화성시정신건강복지센터031-352-017518588경기도 화성시 향남읍 도이리 668번지경기도 화성시 향남읍 향남로 47037.137863126.922411