Overview

Dataset statistics

Number of variables7
Number of observations199
Missing cells17
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory59.7 B

Variable types

Numeric3
Text4

Dataset

Description인천광역시 미추홀구의 약국 현황에 대한 데이터로 약국명칭, 도로명주소,전화번호,위경도 등의 정보를 제공하고 있습니다
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15051494/fileData.do

Alerts

전화번호 has 4 (2.0%) missing valuesMissing
지번주소 has 13 (6.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:15:30.499831
Analysis finished2024-04-06 08:15:34.433800
Duration3.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100
Minimum1
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:15:34.667722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.9
Q150.5
median100
Q3149.5
95-th percentile189.1
Maximum199
Range198
Interquartile range (IQR)99

Descriptive statistics

Standard deviation57.590508
Coefficient of variation (CV)0.57590508
Kurtosis-1.2
Mean100
Median Absolute Deviation (MAD)50
Skewness0
Sum19900
Variance3316.6667
MonotonicityStrictly increasing
2024-04-06T17:15:35.467502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
138 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
Other values (189) 189
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%

약국명칭
Text

Distinct196
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T17:15:36.039918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.3718593
Min length3

Characters and Unicode

Total characters1069
Distinct characters201
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)97.0%

Sample

1st row다정한온누리약국
2nd row1층바로약국
3rd row팜프라자365약국
4th row초록약국
5th row도담약국
ValueCountFrequency (%)
건강프라자약국 2
 
1.0%
약국 2
 
1.0%
유원소망약국 2
 
1.0%
르네상스약국 2
 
1.0%
종로사약국 1
 
0.5%
늘푸른약국 1
 
0.5%
라성약국 1
 
0.5%
고일약국 1
 
0.5%
큰나무약국 1
 
0.5%
을지약국 1
 
0.5%
Other values (188) 188
93.1%
2024-04-06T17:15:37.052272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 200
 
18.7%
국 199
 
18.6%
리 23
 
2.2%
온 16
 
1.5%
누 15
 
1.4%
사 14
 
1.3%
성 14
 
1.3%
랑 13
 
1.2%
안 12
 
1.1%
건 12
 
1.1%
Other values (191) 551
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1045
97.8%
Decimal Number 9
 
0.8%
Uppercase Letter 5
 
0.5%
Space Separator 3
 
0.3%
Lowercase Letter 3
 
0.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 200
 
19.1%
국 199
 
19.0%
리 23
 
2.2%
온 16
 
1.5%
누 15
 
1.4%
사 14
 
1.3%
성 14
 
1.3%
랑 13
 
1.2%
안 12
 
1.1%
건 12
 
1.1%
Other values (176) 527
50.4%
Uppercase Letter
ValueCountFrequency (%)
P 1
20.0%
I 1
20.0%
V 1
20.0%
H 1
20.0%
D 1
20.0%
Decimal Number
ValueCountFrequency (%)
6 3
33.3%
5 3
33.3%
3 2
22.2%
1 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1045
97.8%
Common 16
 
1.5%
Latin 8
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 200
 
19.1%
국 199
 
19.0%
리 23
 
2.2%
온 16
 
1.5%
누 15
 
1.4%
사 14
 
1.3%
성 14
 
1.3%
랑 13
 
1.2%
안 12
 
1.1%
건 12
 
1.1%
Other values (176) 527
50.4%
Latin
ValueCountFrequency (%)
P 1
12.5%
I 1
12.5%
V 1
12.5%
w 1
12.5%
e 1
12.5%
n 1
12.5%
H 1
12.5%
D 1
12.5%
Common
ValueCountFrequency (%)
3
18.8%
6 3
18.8%
5 3
18.8%
3 2
12.5%
( 2
12.5%
) 2
12.5%
1 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1045
97.8%
ASCII 24
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 200
 
19.1%
국 199
 
19.0%
리 23
 
2.2%
온 16
 
1.5%
누 15
 
1.4%
사 14
 
1.3%
성 14
 
1.3%
랑 13
 
1.2%
안 12
 
1.1%
건 12
 
1.1%
Other values (176) 527
50.4%
ASCII
ValueCountFrequency (%)
3
12.5%
6 3
12.5%
5 3
12.5%
3 2
 
8.3%
( 2
 
8.3%
) 2
 
8.3%
P 1
 
4.2%
I 1
 
4.2%
V 1
 
4.2%
1 1
 
4.2%
Other values (5) 5
20.8%

도로명주소
Text

Distinct196
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T17:15:37.632868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length46
Mean length30.452261
Min length23

Characters and Unicode

Total characters6060
Distinct characters169
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)97.0%

Sample

1st row인천광역시 미추홀구 매소홀로 466, 1층 (학익동)
2nd row인천광역시 미추홀구 경인로 372, 포레나 미추홀 201동 1017호 (주안동, 포레나 미추홀)
3rd row인천광역시 미추홀구 숙골로88번길 12, 1-54,55호 (도화동, 더샵 인천스카이타워 1단지)
4th row인천광역시 미추홀구 독배로 395, 와이지메디컬센터 108호 (용현동)
5th row인천광역시 미추홀구 독배로 399, 영광프라자 109호 (용현동)
ValueCountFrequency (%)
인천광역시 199
16.8%
미추홀구 199
16.8%
주안동 84
 
7.1%
1층 63
 
5.3%
용현동 49
 
4.1%
숭의동 22
 
1.9%
경인로 21
 
1.8%
도화동 20
 
1.7%
학익동 16
 
1.4%
석정로 15
 
1.3%
Other values (297) 497
41.9%
2024-04-06T17:15:38.951929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
997
 
16.5%
인 265
 
4.4%
1 244
 
4.0%
홀 233
 
3.8%
미 230
 
3.8%
추 227
 
3.7%
동 207
 
3.4%
천 204
 
3.4%
) 201
 
3.3%
( 201
 
3.3%
Other values (159) 3051
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3623
59.8%
Space Separator 997
 
16.5%
Decimal Number 876
 
14.5%
Close Punctuation 201
 
3.3%
Open Punctuation 201
 
3.3%
Other Punctuation 132
 
2.2%
Dash Punctuation 24
 
0.4%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 265
 
7.3%
홀 233
 
6.4%
미 230
 
6.3%
추 227
 
6.3%
동 207
 
5.7%
천 204
 
5.6%
시 201
 
5.5%
구 200
 
5.5%
역 200
 
5.5%
광 200
 
5.5%
Other values (138) 1456
40.2%
Decimal Number
ValueCountFrequency (%)
1 244
27.9%
2 100
11.4%
3 99
11.3%
0 84
 
9.6%
4 70
 
8.0%
6 68
 
7.8%
5 61
 
7.0%
7 54
 
6.2%
8 49
 
5.6%
9 47
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
16.7%
A 1
16.7%
N 1
16.7%
P 1
16.7%
I 1
16.7%
E 1
16.7%
Space Separator
ValueCountFrequency (%)
997
100.0%
Close Punctuation
ValueCountFrequency (%)
) 201
100.0%
Open Punctuation
ValueCountFrequency (%)
( 201
100.0%
Other Punctuation
ValueCountFrequency (%)
, 132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3623
59.8%
Common 2431
40.1%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 265
 
7.3%
홀 233
 
6.4%
미 230
 
6.3%
추 227
 
6.3%
동 207
 
5.7%
천 204
 
5.6%
시 201
 
5.5%
구 200
 
5.5%
역 200
 
5.5%
광 200
 
5.5%
Other values (138) 1456
40.2%
Common
ValueCountFrequency (%)
997
41.0%
1 244
 
10.0%
) 201
 
8.3%
( 201
 
8.3%
, 132
 
5.4%
2 100
 
4.1%
3 99
 
4.1%
0 84
 
3.5%
4 70
 
2.9%
6 68
 
2.8%
Other values (5) 235
 
9.7%
Latin
ValueCountFrequency (%)
C 1
16.7%
A 1
16.7%
N 1
16.7%
P 1
16.7%
I 1
16.7%
E 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3623
59.8%
ASCII 2437
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
997
40.9%
1 244
 
10.0%
) 201
 
8.2%
( 201
 
8.2%
, 132
 
5.4%
2 100
 
4.1%
3 99
 
4.1%
0 84
 
3.4%
4 70
 
2.9%
6 68
 
2.8%
Other values (11) 241
 
9.9%
Hangul
ValueCountFrequency (%)
인 265
 
7.3%
홀 233
 
6.4%
미 230
 
6.3%
추 227
 
6.3%
동 207
 
5.7%
천 204
 
5.6%
시 201
 
5.5%
구 200
 
5.5%
역 200
 
5.5%
광 200
 
5.5%
Other values (138) 1456
40.2%

전화번호
Text

MISSING 

Distinct192
Distinct (%)98.5%
Missing4
Missing (%)2.0%
Memory size1.7 KiB
2024-04-06T17:15:39.561520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.035897
Min length12

Characters and Unicode

Total characters2347
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

Unique189 ?
Unique (%)96.9%

Sample

1st row032-872-8544
2nd row032-433-2990
3rd row0507-1357-2664
4th row032-503-7052
5th row032-547-4858
ValueCountFrequency (%)
032-420-0457 2
 
1.0%
032-429-7888 2
 
1.0%
032-885-3929 2
 
1.0%
032-425-3632 1
 
0.5%
032-873-8087 1
 
0.5%
032-884-4674 1
 
0.5%
032-868-8066 1
 
0.5%
032-432-5639 1
 
0.5%
032-876-0197 1
 
0.5%
032-438-3667 1
 
0.5%
Other values (182) 182
93.3%
2024-04-06T17:15:40.499591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 390
16.6%
2 335
14.3%
0 306
13.0%
3 306
13.0%
8 274
11.7%
7 150
 
6.4%
4 133
 
5.7%
5 131
 
5.6%
6 117
 
5.0%
1 111
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1957
83.4%
Dash Punctuation 390
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 335
17.1%
0 306
15.6%
3 306
15.6%
8 274
14.0%
7 150
7.7%
4 133
 
6.8%
5 131
 
6.7%
6 117
 
6.0%
1 111
 
5.7%
9 94
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 390
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2347
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 390
16.6%
2 335
14.3%
0 306
13.0%
3 306
13.0%
8 274
11.7%
7 150
 
6.4%
4 133
 
5.7%
5 131
 
5.6%
6 117
 
5.0%
1 111
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 390
16.6%
2 335
14.3%
0 306
13.0%
3 306
13.0%
8 274
11.7%
7 150
 
6.4%
4 133
 
5.7%
5 131
 
5.6%
6 117
 
5.0%
1 111
 
4.7%

지번주소
Text

MISSING 

Distinct179
Distinct (%)96.2%
Missing13
Missing (%)6.5%
Memory size1.7 KiB
2024-04-06T17:15:41.060620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length25.096774
Min length18

Characters and Unicode

Total characters4668
Distinct characters155
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)94.1%

Sample

1st row인천광역시 미추홀구 학익동 661-1
2nd row인천광역시 미추홀구 주안동 0 포레나 미추홀
3rd row인천광역시 미추홀구 도화동 1011 더샵 인천스카이타워 1단지
4th row인천광역시 미추홀구 용현동 0 와이지메디컬센터
5th row인천광역시 미추홀구 용현동 0 영광프라자 109호
ValueCountFrequency (%)
인천광역시 186
21.2%
미추홀구 186
21.2%
주안동 55
 
6.3%
용현동 39
 
4.4%
숭의동 16
 
1.8%
학익동 14
 
1.6%
1층 14
 
1.6%
도화동 11
 
1.3%
주안1동 8
 
0.9%
0 8
 
0.9%
Other values (275) 341
38.8%
2024-04-06T17:15:41.930184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
736
 
15.8%
1 232
 
5.0%
미 195
 
4.2%
인 194
 
4.2%
추 192
 
4.1%
홀 192
 
4.1%
동 192
 
4.1%
천 192
 
4.1%
시 188
 
4.0%
광 187
 
4.0%
Other values (145) 2168
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2828
60.6%
Decimal Number 948
 
20.3%
Space Separator 736
 
15.8%
Dash Punctuation 136
 
2.9%
Uppercase Letter 9
 
0.2%
Other Punctuation 5
 
0.1%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 195
 
6.9%
인 194
 
6.9%
추 192
 
6.8%
홀 192
 
6.8%
동 192
 
6.8%
천 192
 
6.8%
시 188
 
6.6%
광 187
 
6.6%
역 187
 
6.6%
구 186
 
6.6%
Other values (122) 923
32.6%
Decimal Number
ValueCountFrequency (%)
1 232
24.5%
2 113
11.9%
4 94
9.9%
6 89
 
9.4%
5 85
 
9.0%
0 83
 
8.8%
3 80
 
8.4%
7 62
 
6.5%
9 56
 
5.9%
8 54
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
22.2%
I 2
22.2%
A 1
11.1%
V 1
11.1%
N 1
11.1%
E 1
11.1%
C 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
736
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2828
60.6%
Common 1831
39.2%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 195
 
6.9%
인 194
 
6.9%
추 192
 
6.8%
홀 192
 
6.8%
동 192
 
6.8%
천 192
 
6.8%
시 188
 
6.6%
광 187
 
6.6%
역 187
 
6.6%
구 186
 
6.6%
Other values (122) 923
32.6%
Common
ValueCountFrequency (%)
736
40.2%
1 232
 
12.7%
- 136
 
7.4%
2 113
 
6.2%
4 94
 
5.1%
6 89
 
4.9%
5 85
 
4.6%
0 83
 
4.5%
3 80
 
4.4%
7 62
 
3.4%
Other values (6) 121
 
6.6%
Latin
ValueCountFrequency (%)
P 2
22.2%
I 2
22.2%
A 1
11.1%
V 1
11.1%
N 1
11.1%
E 1
11.1%
C 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2828
60.6%
ASCII 1840
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
736
40.0%
1 232
 
12.6%
- 136
 
7.4%
2 113
 
6.1%
4 94
 
5.1%
6 89
 
4.8%
5 85
 
4.6%
0 83
 
4.5%
3 80
 
4.3%
7 62
 
3.4%
Other values (13) 130
 
7.1%
Hangul
ValueCountFrequency (%)
미 195
 
6.9%
인 194
 
6.9%
추 192
 
6.8%
홀 192
 
6.8%
동 192
 
6.8%
천 192
 
6.8%
시 188
 
6.6%
광 187
 
6.6%
역 187
 
6.6%
구 186
 
6.6%
Other values (122) 923
32.6%

위도
Real number (ℝ)

Distinct187
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455707
Minimum37.437384
Maximum37.477956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:15:42.224124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437384
5-th percentile37.441945
Q137.450008
median37.457383
Q337.461076
95-th percentile37.467975
Maximum37.477956
Range0.0405717
Interquartile range (IQR)0.011068505

Descriptive statistics

Standard deviation0.0081080876
Coefficient of variation (CV)0.00021647135
Kurtosis-0.34359795
Mean37.455707
Median Absolute Deviation (MAD)0.00584477
Skewness-0.11224354
Sum7453.6857
Variance6.5741085 × 10-5
MonotonicityNot monotonic
2024-04-06T17:15:42.517107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45826254 5
 
2.5%
37.46039207 3
 
1.5%
37.44999319 2
 
1.0%
37.44250623 2
 
1.0%
37.45828798 2
 
1.0%
37.45659257 2
 
1.0%
37.44768455 2
 
1.0%
37.46167352 2
 
1.0%
37.45519506 1
 
0.5%
37.45823827 1
 
0.5%
Other values (177) 177
88.9%
ValueCountFrequency (%)
37.43738389 1
0.5%
37.43760258 1
0.5%
37.43825665 1
0.5%
37.43926519 1
0.5%
37.43929879 1
0.5%
37.43934765 1
0.5%
37.43953362 1
0.5%
37.44042158 1
0.5%
37.4414509 1
0.5%
37.44184925 1
0.5%
ValueCountFrequency (%)
37.47795559 1
0.5%
37.47697163 1
0.5%
37.47211604 1
0.5%
37.46991797 1
0.5%
37.46954959 1
0.5%
37.4694746 1
0.5%
37.46884775 1
0.5%
37.46857416 1
0.5%
37.46835781 1
0.5%
37.46807119 1
0.5%

경도
Real number (ℝ)

Distinct187
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66732
Minimum126.63327
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:15:42.813333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63327
5-th percentile126.63755
Q1126.6516
median126.67178
Q3126.68045
95-th percentile126.68983
Maximum126.70152
Range0.0682483
Interquartile range (IQR)0.02885135

Descriptive statistics

Standard deviation0.017472955
Coefficient of variation (CV)0.00013794367
Kurtosis-1.0429578
Mean126.66732
Median Absolute Deviation (MAD)0.0117672
Skewness-0.34400743
Sum25206.797
Variance0.00030530416
MonotonicityNot monotonic
2024-04-06T17:15:43.213884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6803069 5
 
2.5%
126.6891379 3
 
1.5%
126.6336714 2
 
1.0%
126.7015187 2
 
1.0%
126.6881584 2
 
1.0%
126.6411399 2
 
1.0%
126.6809393 2
 
1.0%
126.6433975 2
 
1.0%
126.6575835 1
 
0.5%
126.6884075 1
 
0.5%
Other values (177) 177
88.9%
ValueCountFrequency (%)
126.6332704 1
0.5%
126.6336714 2
1.0%
126.6356716 1
0.5%
126.6357748 1
0.5%
126.6359595 1
0.5%
126.6360296 1
0.5%
126.6372363 1
0.5%
126.6372774 1
0.5%
126.6375369 1
0.5%
126.6375535 1
0.5%
ValueCountFrequency (%)
126.7015187 2
1.0%
126.6969867 1
0.5%
126.6950864 1
0.5%
126.694756 1
0.5%
126.6941699 1
0.5%
126.6937389 1
0.5%
126.6934638 1
0.5%
126.6910227 1
0.5%
126.6898433 1
0.5%
126.6898253 1
0.5%

Interactions

2024-04-06T17:15:32.625325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:31.220679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:32.046335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:32.903689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:31.596046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:32.245838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:33.092083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:31.816817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:15:32.437556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:15:43.403333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.3550.352
위도0.3551.0000.777
경도0.3520.7771.000
2024-04-06T17:15:43.567095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.0380.013
위도-0.0381.0000.035
경도0.0130.0351.000

Missing values

2024-04-06T17:15:33.420615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:15:33.845329image/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.
2024-04-06T17:15:34.304631image/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

연번약국명칭도로명주소전화번호지번주소위도경도
01다정한온누리약국인천광역시 미추홀구 매소홀로 466, 1층 (학익동)032-872-8544인천광역시 미추홀구 학익동 661-137.439348126.673637
121층바로약국인천광역시 미추홀구 경인로 372, 포레나 미추홀 201동 1017호 (주안동, 포레나 미추홀)032-433-2990인천광역시 미추홀구 주안동 0 포레나 미추홀37.458263126.680307
23팜프라자365약국인천광역시 미추홀구 숙골로88번길 12, 1-54,55호 (도화동, 더샵 인천스카이타워 1단지)<NA>인천광역시 미추홀구 도화동 1011 더샵 인천스카이타워 1단지37.46955126.664539
34초록약국인천광역시 미추홀구 독배로 395, 와이지메디컬센터 108호 (용현동)0507-1357-2664인천광역시 미추홀구 용현동 0 와이지메디컬센터37.455155126.648936
45도담약국인천광역시 미추홀구 독배로 399, 영광프라자 109호 (용현동)032-503-7052인천광역시 미추홀구 용현동 0 영광프라자 109호37.455382126.649179
56효성약국인천광역시 미추홀구 한나루로 499-3, 1층 (용현동)032-547-4858인천광역시 미추홀구 용현동 7-437.451553126.667131
67아플때약국인천광역시 미추홀구 인하로221번길 6, 102호 (주안동)032-710-4430인천광역시 미추홀구 주안동 1420-4437.448731126.673015
78미추홀온누리약국인천광역시 미추홀구 염전로168번길 15, 107,108호 (도화동)032-719-3737인천광역시 미추홀구 도화동 986-237.476972126.660872
89서울약국인천광역시 미추홀구 독정이로 25-1 (용현동)032-887-7841인천광역시 미추홀구 용현동 492-18737.458215126.653921
910주안열린약국인천광역시 미추홀구 미추홀대로 610, 110,111호 (주안동)070-8657-1237인천광역시 미추홀구 주안동 1469-137.451699126.680033
연번약국명칭도로명주소전화번호지번주소위도경도
189190우일약국인천광역시 미추홀구 동주길135번길 20-6 (주안동)032-425-2958인천광역시 미추홀구 주안4동 409-1337.457492126.683961
190191길정약국인천광역시 미추홀구 인주대로 261 (주안동)032-862-1069인천광역시 미추홀구 주안2동 677-437.45303126.665792
191192정성약국인천광역시 미추홀구 신기길58번길 43-3 (주안동)032-873-0931인천광역시 미추홀구 주안3동 869-7137.445447126.674386
192193한신약국인천광역시 미추홀구 경원대로 717 (주안동)032-422-9578인천광역시 미추홀구 주안동 1621번지 인천관교한신휴플러스상가에이동 107호37.447083126.685205
193194기성약국인천광역시 미추홀구 낙섬중로 51 (용현동)032-884-2691인천광역시 미추홀구 용현동 622-151번지37.452714126.638152
194195중화약국인천광역시 미추홀구 석정로 16 (숭의동)032-882-2845인천광역시 미추홀구 숭의2동 340-2437.461132126.642538
195196종로사약국인천광역시 미추홀구 경인로 382-1 (주안동)032-425-3632인천광역시 미추홀구 주안4동 434-1137.458125126.682477
196197성우약국인천광역시 미추홀구 한나루로 389, 1층 (학익동)032-883-5752인천광역시 미추홀구 학익동 259-11번지 1층37.442711126.663669
197198만화약국인천광역시 미추홀구 미추로 25 (숭의동)032-883-3446인천광역시 미추홀구 숭의2동 168-137.462389126.646923
198199부영약국인천광역시 미추홀구 한나루로 411 (학익동)032-875-2391인천광역시 미추홀구 학익동 262-10번지37.444393126.665029