Overview

Dataset statistics

Number of variables11
Number of observations342
Missing cells106
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.5 KiB
Average record size in memory91.4 B

Variable types

Numeric3
Categorical4
Text3
DateTime1

Dataset

Description광주광역시 광산구 관내 약국, 보건소, 경로당, 행정복지센터 등에 위치한 폐의약품 수거함 현황 정보(시도명, 시군구명, 구분, 설치장소명, 주소, 위도, 경도, 전화번호 등)를 제공합니다.
Author광주광역시 광산구
URLhttps://www.data.go.kr/data/15108779/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
관리부서명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 연번High correlation
구분 is highly overall correlated with 연번High correlation
위도 has 45 (13.2%) missing valuesMissing
경도 has 45 (13.2%) missing valuesMissing
전화번호 has 16 (4.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:11:31.136485
Analysis finished2023-12-12 03:11:33.742508
Duration2.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct342
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.5
Minimum1
Maximum342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T12:11:33.822051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.05
Q186.25
median171.5
Q3256.75
95-th percentile324.95
Maximum342
Range341
Interquartile range (IQR)170.5

Descriptive statistics

Standard deviation98.871128
Coefficient of variation (CV)0.57650804
Kurtosis-1.2
Mean171.5
Median Absolute Deviation (MAD)85.5
Skewness0
Sum58653
Variance9775.5
MonotonicityStrictly increasing
2023-12-12T12:11:34.019176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
227 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
Other values (332) 332
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%
335 1
0.3%
334 1
0.3%
333 1
0.3%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
광주광역시
342 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주광역시 342
100.0%

Length

2023-12-12T12:11:34.218572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:34.349799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주광역시 342
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
광산구
342 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광산구 342
100.0%

Length

2023-12-12T12:11:34.481827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:34.610195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광산구 342
100.0%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
약국
165 
경로당
145 
행정복지센터
21 
보건소
 
11

Length

Max length6
Median length3
Mean length2.7017544
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
약국 165
48.2%
경로당 145
42.4%
행정복지센터 21
 
6.1%
보건소 11
 
3.2%

Length

2023-12-12T12:11:34.738809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:34.915128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
약국 165
48.2%
경로당 145
42.4%
행정복지센터 21
 
6.1%
보건소 11
 
3.2%

설치장소명
Text

Distinct337
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T12:11:35.209635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.2573099
Min length2

Characters and Unicode

Total characters1798
Distinct characters235
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

Unique333 ?
Unique (%)97.4%

Sample

1st row은성약국
2nd row솔빛약국
3rd row수한약국
4th row정원약국
5th row하나약국
ValueCountFrequency (%)
본촌경로당 3
 
0.9%
약국 3
 
0.9%
봉정경로당 2
 
0.6%
동산경로당 2
 
0.6%
신기경로당 2
 
0.6%
지정경로당 1
 
0.3%
지평경로당 1
 
0.3%
송학경로당 1
 
0.3%
회룡경로당 1
 
0.3%
송산경로당 1
 
0.3%
Other values (334) 334
95.2%
2023-12-12T12:11:35.719642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 167
 
9.3%
국 165
 
9.2%
로 160
 
8.9%
당 151
 
8.4%
경 145
 
8.1%
동 55
 
3.1%
산 30
 
1.7%
신 23
 
1.3%
21
 
1.2%
건 19
 
1.1%
Other values (225) 862
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1757
97.7%
Space Separator 21
 
1.2%
Decimal Number 17
 
0.9%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 167
 
9.5%
국 165
 
9.4%
로 160
 
9.1%
당 151
 
8.6%
경 145
 
8.3%
동 55
 
3.1%
산 30
 
1.7%
신 23
 
1.3%
건 19
 
1.1%
정 19
 
1.1%
Other values (217) 823
46.8%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
1 5
29.4%
6 2
 
11.8%
3 2
 
11.8%
5 2
 
11.8%
4 1
 
5.9%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1757
97.7%
Common 41
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 167
 
9.5%
국 165
 
9.4%
로 160
 
9.1%
당 151
 
8.6%
경 145
 
8.3%
동 55
 
3.1%
산 30
 
1.7%
신 23
 
1.3%
건 19
 
1.1%
정 19
 
1.1%
Other values (217) 823
46.8%
Common
ValueCountFrequency (%)
21
51.2%
2 5
 
12.2%
1 5
 
12.2%
. 3
 
7.3%
6 2
 
4.9%
3 2
 
4.9%
5 2
 
4.9%
4 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1757
97.7%
ASCII 41
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 167
 
9.5%
국 165
 
9.4%
로 160
 
9.1%
당 151
 
8.6%
경 145
 
8.3%
동 55
 
3.1%
산 30
 
1.7%
신 23
 
1.3%
건 19
 
1.1%
정 19
 
1.1%
Other values (217) 823
46.8%
ASCII
ValueCountFrequency (%)
21
51.2%
2 5
 
12.2%
1 5
 
12.2%
. 3
 
7.3%
6 2
 
4.9%
3 2
 
4.9%
5 2
 
4.9%
4 1
 
2.4%

주소
Text

Distinct340
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2023-12-12T12:11:36.178746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length45
Mean length26.157895
Min length16

Characters and Unicode

Total characters8946
Distinct characters192
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338 ?
Unique (%)98.8%

Sample

1st row광주광역시 광산구 상무대로 260, 1층 (송정동)
2nd row광주광역시 광산구 손재로110번길 35, 102호 (하남동)
3rd row광주광역시 광산구 목련로 74, 1층 (산정동)
4th row광주광역시 광산구 풍영로 261, 1층 104호 (장덕동)
5th row광주광역시 광산구 목련로 89, 101호 (월곡동)
ValueCountFrequency (%)
광주광역시 342
 
18.8%
광산구 341
 
18.7%
1층 69
 
3.8%
송정동 24
 
1.3%
임방울대로 18
 
1.0%
월곡동 16
 
0.9%
운남동 15
 
0.8%
월계동 14
 
0.8%
우산동 14
 
0.8%
수완동 12
 
0.7%
Other values (555) 954
52.4%
2023-12-12T12:11:36.885917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1480
16.5%
광 1038
 
11.6%
산 452
 
5.1%
동 371
 
4.1%
1 361
 
4.0%
주 348
 
3.9%
시 345
 
3.9%
역 342
 
3.8%
구 342
 
3.8%
( 300
 
3.4%
Other values (182) 3567
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5381
60.1%
Space Separator 1480
 
16.5%
Decimal Number 1298
 
14.5%
Open Punctuation 300
 
3.4%
Close Punctuation 300
 
3.4%
Other Punctuation 122
 
1.4%
Dash Punctuation 62
 
0.7%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 1038
19.3%
산 452
 
8.4%
동 371
 
6.9%
주 348
 
6.5%
시 345
 
6.4%
역 342
 
6.4%
구 342
 
6.4%
로 227
 
4.2%
길 180
 
3.3%
층 73
 
1.4%
Other values (164) 1663
30.9%
Decimal Number
ValueCountFrequency (%)
1 361
27.8%
2 191
14.7%
0 121
 
9.3%
3 116
 
8.9%
5 105
 
8.1%
7 101
 
7.8%
6 90
 
6.9%
4 84
 
6.5%
9 68
 
5.2%
8 61
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
1480
100.0%
Open Punctuation
ValueCountFrequency (%)
( 300
100.0%
Close Punctuation
ValueCountFrequency (%)
) 300
100.0%
Other Punctuation
ValueCountFrequency (%)
, 122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5381
60.1%
Common 3563
39.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 1038
19.3%
산 452
 
8.4%
동 371
 
6.9%
주 348
 
6.5%
시 345
 
6.4%
역 342
 
6.4%
구 342
 
6.4%
로 227
 
4.2%
길 180
 
3.3%
층 73
 
1.4%
Other values (164) 1663
30.9%
Common
ValueCountFrequency (%)
1480
41.5%
1 361
 
10.1%
( 300
 
8.4%
) 300
 
8.4%
2 191
 
5.4%
, 122
 
3.4%
0 121
 
3.4%
3 116
 
3.3%
5 105
 
2.9%
7 101
 
2.8%
Other values (6) 366
 
10.3%
Latin
ValueCountFrequency (%)
C 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5381
60.1%
ASCII 3565
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1480
41.5%
1 361
 
10.1%
( 300
 
8.4%
) 300
 
8.4%
2 191
 
5.4%
, 122
 
3.4%
0 121
 
3.4%
3 116
 
3.3%
5 105
 
2.9%
7 101
 
2.8%
Other values (8) 368
 
10.3%
Hangul
ValueCountFrequency (%)
광 1038
19.3%
산 452
 
8.4%
동 371
 
6.9%
주 348
 
6.5%
시 345
 
6.4%
역 342
 
6.4%
구 342
 
6.4%
로 227
 
4.2%
길 180
 
3.3%
층 73
 
1.4%
Other values (164) 1663
30.9%

위도
Real number (ℝ)

MISSING 

Distinct292
Distinct (%)98.3%
Missing45
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean35.171441
Minimum35.074191
Maximum35.25084
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T12:11:37.108720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.074191
5-th percentile35.107616
Q135.141588
median35.176354
Q335.19553
95-th percentile35.22053
Maximum35.25084
Range0.1766489
Interquartile range (IQR)0.053942

Descriptive statistics

Standard deviation0.035165185
Coefficient of variation (CV)0.00099982212
Kurtosis-0.48898037
Mean35.171441
Median Absolute Deviation (MAD)0.0251098
Skewness-0.41243024
Sum10445.918
Variance0.0012365902
MonotonicityNot monotonic
2023-12-12T12:11:37.328364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.2138357 2
 
0.6%
35.1653024 2
 
0.6%
35.1970619 2
 
0.6%
35.1413427 2
 
0.6%
35.1031047 2
 
0.6%
35.1072993 1
 
0.3%
35.1216218 1
 
0.3%
35.1144276 1
 
0.3%
35.1344297 1
 
0.3%
35.1268413 1
 
0.3%
Other values (282) 282
82.5%
(Missing) 45
 
13.2%
ValueCountFrequency (%)
35.0741909 1
0.3%
35.0835844 1
0.3%
35.0868131 1
0.3%
35.0870362 1
0.3%
35.0918136 1
0.3%
35.0985782 1
0.3%
35.0993062 1
0.3%
35.0994914 1
0.3%
35.0996213 1
0.3%
35.1005634 1
0.3%
ValueCountFrequency (%)
35.2508398 1
0.3%
35.2363803 1
0.3%
35.2326202 1
0.3%
35.230947 1
0.3%
35.2258269 1
0.3%
35.2241915 1
0.3%
35.2221715 1
0.3%
35.2221046 1
0.3%
35.2219976 1
0.3%
35.2219292 1
0.3%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct292
Distinct (%)98.3%
Missing45
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean126.78333
Minimum126.66028
Maximum126.85226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-12T12:11:37.564745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.66028
5-th percentile126.68896
Q1126.74811
median126.79536
Q3126.82261
95-th percentile126.8437
Maximum126.85226
Range0.1919813
Interquartile range (IQR)0.0744996

Descriptive statistics

Standard deviation0.048830897
Coefficient of variation (CV)0.00038515234
Kurtosis-0.43222176
Mean126.78333
Median Absolute Deviation (MAD)0.0303781
Skewness-0.72870816
Sum37654.649
Variance0.0023844565
MonotonicityNot monotonic
2023-12-12T12:11:37.815965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8434621 2
 
0.6%
126.8032068 2
 
0.6%
126.8257351 2
 
0.6%
126.7948997 2
 
0.6%
126.7929291 2
 
0.6%
126.788732 1
 
0.3%
126.6957522 1
 
0.3%
126.7218649 1
 
0.3%
126.7805399 1
 
0.3%
126.7540694 1
 
0.3%
Other values (282) 282
82.5%
(Missing) 45
 
13.2%
ValueCountFrequency (%)
126.6602762 1
0.3%
126.660762 1
0.3%
126.6631257 1
0.3%
126.6633629 1
0.3%
126.6653302 1
0.3%
126.6673244 1
0.3%
126.6757062 1
0.3%
126.6779084 1
0.3%
126.6781723 1
0.3%
126.6794021 1
0.3%
ValueCountFrequency (%)
126.8522575 1
0.3%
126.8505774 1
0.3%
126.8499674 1
0.3%
126.8498719 1
0.3%
126.8492672 1
0.3%
126.8490147 1
0.3%
126.8487185 1
0.3%
126.8464971 1
0.3%
126.8462225 1
0.3%
126.8461555 1
0.3%

전화번호
Text

MISSING 

Distinct325
Distinct (%)99.7%
Missing16
Missing (%)4.7%
Memory size2.8 KiB
2023-12-12T12:11:38.162174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.003067
Min length12

Characters and Unicode

Total characters3913
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

Unique324 ?
Unique (%)99.4%

Sample

1st row062-431-8900
2nd row062-951-7050
3rd row062-651-5197
4th row062-951-0200
5th row062-945-6354
ValueCountFrequency (%)
062-943-0708 2
 
0.6%
062-944-3660 1
 
0.3%
062-943-6446 1
 
0.3%
062-943-2250 1
 
0.3%
062-943-0006 1
 
0.3%
062-943-7373 1
 
0.3%
062-944-6768 1
 
0.3%
062-944-5944 1
 
0.3%
062-943-3437 1
 
0.3%
062-943-0360 1
 
0.3%
Other values (315) 315
96.6%
2023-12-12T12:11:38.705523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 652
16.7%
2 527
13.5%
0 516
13.2%
6 500
12.8%
9 417
10.7%
5 294
7.5%
4 291
7.4%
3 211
 
5.4%
7 203
 
5.2%
1 165
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3261
83.3%
Dash Punctuation 652
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 527
16.2%
0 516
15.8%
6 500
15.3%
9 417
12.8%
5 294
9.0%
4 291
8.9%
3 211
6.5%
7 203
 
6.2%
1 165
 
5.1%
8 137
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 652
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 652
16.7%
2 527
13.5%
0 516
13.2%
6 500
12.8%
9 417
10.7%
5 294
7.5%
4 291
7.4%
3 211
 
5.4%
7 203
 
5.2%
1 165
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 652
16.7%
2 527
13.5%
0 516
13.2%
6 500
12.8%
9 417
10.7%
5 294
7.5%
4 291
7.4%
3 211
 
5.4%
7 203
 
5.2%
1 165
 
4.2%

관리부서명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
보건행정과
342 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건행정과 342
100.0%

Length

2023-12-12T12:11:38.853430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:11:38.976312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건행정과 342
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2023-11-10 00:00:00
Maximum2023-11-10 00:00:00
2023-12-12T12:11:39.082470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:39.192875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T12:11:32.838522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:31.688450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:32.456855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:32.979522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:31.810691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:32.580538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:33.103380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:31.931531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:11:32.703615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:11:39.276136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분위도경도
연번1.0000.8960.6420.777
구분0.8961.0000.3800.700
위도0.6420.3801.0000.785
경도0.7770.7000.7851.000
2023-12-12T12:11:39.401641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도구분
연번1.000-0.202-0.6200.768
위도-0.2021.0000.4190.233
경도-0.6200.4191.0000.497
구분0.7680.2330.4971.000

Missing values

2023-12-12T12:11:33.278110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:11:33.497962image/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.
2023-12-12T12:11:33.666651image/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

연번시도명시군구명구분설치장소명주소위도경도전화번호관리부서명데이터기준일자
01광주광역시광산구약국은성약국광주광역시 광산구 상무대로 260, 1층 (송정동)35.141588126.795083062-431-8900보건행정과2023-11-10
12광주광역시광산구약국솔빛약국광주광역시 광산구 손재로110번길 35, 102호 (하남동)35.176354126.798752062-951-7050보건행정과2023-11-10
23광주광역시광산구약국수한약국광주광역시 광산구 목련로 74, 1층 (산정동)35.17216126.80573<NA>보건행정과2023-11-10
34광주광역시광산구약국정원약국광주광역시 광산구 풍영로 261, 1층 104호 (장덕동)35.194617126.815361062-651-5197보건행정과2023-11-10
45광주광역시광산구약국하나약국광주광역시 광산구 목련로 89, 101호 (월곡동)35.172393126.807483062-951-0200보건행정과2023-11-10
56광주광역시광산구약국우리약국광주광역시 광산구 동곡로 739, 105호 (선암동)35.147518126.777886062-945-6354보건행정과2023-11-10
67광주광역시광산구약국수완유약국광주광역시 광산구 임방울대로 348, 106호 (수완동)35.191126126.824338062-959-7585보건행정과2023-11-10
78광주광역시광산구약국라임약국광주광역시 광산구 수등로 270 (신가동)35.184979126.838337062-956-3646보건행정과2023-11-10
89광주광역시광산구약국소원약국광주광역시 광산구 수등로 238 (신가동)35.184937126.834968062-953-2757보건행정과2023-11-10
910광주광역시광산구약국대성약국광주광역시 광산구 광산로29번길 18 (송정동)35.140118126.794073062-945-9532보건행정과2023-11-10
연번시도명시군구명구분설치장소명주소위도경도전화번호관리부서명데이터기준일자
332333광주광역시광산구보건소수완건강생활지원센터광주광역시 광산구 사암로 16735.159315126.807564<NA>보건행정과2023-11-10
333334광주광역시광산구보건소우산건강생활지원센터광주광역시 광산구 장덕로 15835.197062126.825735<NA>보건행정과2023-11-10
334335광주광역시광산구보건소송정보건지소광주광역시 광산구 광산로29번길 15, 1층<NA><NA>062-616-5828보건행정과2023-11-10
335336광주광역시광산구보건소신동보건진료소광주광역시 광산구 신동산길 117<NA><NA>062-943-2935보건행정과2023-11-10
336337광주광역시광산구보건소양동보건진료소광주광역시 광산구 체암로 1745<NA><NA>062-943-7946보건행정과2023-11-10
337338광주광역시광산구보건소신룡보건진료소광주광역시 광산구 임곡신촌길 35<NA><NA>062-952-7653보건행정과2023-11-10
338339광주광역시광산구보건소광산보건지료소광주광역시 광산구 오룡동길 54(광산동)<NA><NA>062-952-1610보건행정과2023-11-10
339340광주광역시광산구보건소동호보건진료소광주광역시 광산구 본동로 363-10<NA><NA>062-943-1156보건행정과2023-11-10
340341광주광역시광산구보건소명화보건진료소광주광역시 광산구 평동로 427<NA><NA>062-943-0013보건행정과2023-11-10
341342광주광역시광산구보건소산수보건진료소광주광역시 광산구 본량용강길 10<NA><NA>062-944-4549보건행정과2023-11-10