Overview

Dataset statistics

Number of variables7
Number of observations190
Missing cells18
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 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://data.incheon.go.kr/findData/publicDataDetail?dataId=15051494&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 4 (2.1%) missing valuesMissing
지번주소 has 14 (7.4%) missing valuesMissing
연번 has unique valuesUnique
약국명칭 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-18 03:20:02.321832
Analysis finished2024-03-18 03:20:04.205272
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.5
Minimum1
Maximum190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-18T12:20:04.265497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.45
Q148.25
median95.5
Q3142.75
95-th percentile180.55
Maximum190
Range189
Interquartile range (IQR)94.5

Descriptive statistics

Standard deviation54.992424
Coefficient of variation (CV)0.5758369
Kurtosis-1.2
Mean95.5
Median Absolute Deviation (MAD)47.5
Skewness0
Sum18145
Variance3024.1667
MonotonicityStrictly increasing
2024-03-18T12:20:04.381925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
132 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
Other values (180) 180
94.7%
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 (%)
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%

약국명칭
Text

UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-18T12:20:04.629064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.3105263
Min length3

Characters and Unicode

Total characters1009
Distinct characters195
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

Unique190 ?
Unique (%)100.0%

Sample

1st row인하후문약국
2nd row뉴아인약국
3rd row코뿔소약국
4th row동신온누리약국
5th row아이사랑약국
ValueCountFrequency (%)
약국 2
 
1.0%
인하후문약국 1
 
0.5%
제일약국 1
 
0.5%
인암종로약국 1
 
0.5%
용현독일약국 1
 
0.5%
용현우리약국 1
 
0.5%
우성약국 1
 
0.5%
우일약국 1
 
0.5%
운현약국 1
 
0.5%
위드팜굿모닝약국 1
 
0.5%
Other values (182) 182
94.3%
2024-03-18T12:20:04.994537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 191
 
18.9%
국 190
 
18.8%
리 21
 
2.1%
사 14
 
1.4%
성 14
 
1.4%
온 14
 
1.4%
랑 13
 
1.3%
누 13
 
1.3%
건 12
 
1.2%
디 11
 
1.1%
Other values (185) 516
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 989
98.0%
Decimal Number 5
 
0.5%
Uppercase Letter 5
 
0.5%
Space Separator 3
 
0.3%
Lowercase Letter 3
 
0.3%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 191
 
19.3%
국 190
 
19.2%
리 21
 
2.1%
사 14
 
1.4%
성 14
 
1.4%
온 14
 
1.4%
랑 13
 
1.3%
누 13
 
1.3%
건 12
 
1.2%
디 11
 
1.1%
Other values (171) 496
50.2%
Uppercase Letter
ValueCountFrequency (%)
V 1
20.0%
I 1
20.0%
P 1
20.0%
D 1
20.0%
H 1
20.0%
Decimal Number
ValueCountFrequency (%)
5 2
40.0%
6 2
40.0%
3 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 989
98.0%
Common 12
 
1.2%
Latin 8
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 191
 
19.3%
국 190
 
19.2%
리 21
 
2.1%
사 14
 
1.4%
성 14
 
1.4%
온 14
 
1.4%
랑 13
 
1.3%
누 13
 
1.3%
건 12
 
1.2%
디 11
 
1.1%
Other values (171) 496
50.2%
Latin
ValueCountFrequency (%)
V 1
12.5%
I 1
12.5%
P 1
12.5%
w 1
12.5%
e 1
12.5%
n 1
12.5%
D 1
12.5%
H 1
12.5%
Common
ValueCountFrequency (%)
3
25.0%
5 2
16.7%
) 2
16.7%
( 2
16.7%
6 2
16.7%
3 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 989
98.0%
ASCII 20
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 191
 
19.3%
국 190
 
19.2%
리 21
 
2.1%
사 14
 
1.4%
성 14
 
1.4%
온 14
 
1.4%
랑 13
 
1.3%
누 13
 
1.3%
건 12
 
1.2%
디 11
 
1.1%
Other values (171) 496
50.2%
ASCII
ValueCountFrequency (%)
3
15.0%
5 2
10.0%
) 2
10.0%
( 2
10.0%
6 2
10.0%
3 1
 
5.0%
V 1
 
5.0%
I 1
 
5.0%
P 1
 
5.0%
w 1
 
5.0%
Other values (4) 4
20.0%

도로명주소
Text

UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-18T12:20:05.248171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length44
Mean length29.663158
Min length23

Characters and Unicode

Total characters5636
Distinct characters165
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

Unique190 ?
Unique (%)100.0%

Sample

1st row인천광역시 미추홀구 인하로 73-1, 1층 우측 (용현동)
2nd row인천광역시 미추홀구 경인로 372, 1014호 (주안동)
3rd row인천광역시 미추홀구 경인로 372, 1018호 (주안동)
4th row인천광역시 미추홀구 소성로 93, 1층 (학익동)
5th row인천광역시 미추홀구 경인로 372, 1011호 (주안동, 포레나 미추홀)
ValueCountFrequency (%)
인천광역시 190
17.1%
미추홀구 190
17.1%
주안동 78
 
7.0%
1층 57
 
5.1%
용현동 47
 
4.2%
숭의동 22
 
2.0%
도화동 20
 
1.8%
경인로 20
 
1.8%
석정로 15
 
1.4%
학익동 15
 
1.4%
Other values (283) 454
41.0%
2024-03-18T12:20:05.613672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
929
 
16.5%
인 253
 
4.5%
홀 217
 
3.9%
미 215
 
3.8%
추 212
 
3.8%
1 210
 
3.7%
동 197
 
3.5%
천 194
 
3.4%
시 192
 
3.4%
( 192
 
3.4%
Other values (155) 2825
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3399
60.3%
Space Separator 929
 
16.5%
Decimal Number 789
 
14.0%
Open Punctuation 192
 
3.4%
Close Punctuation 192
 
3.4%
Other Punctuation 108
 
1.9%
Dash Punctuation 21
 
0.4%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 253
 
7.4%
홀 217
 
6.4%
미 215
 
6.3%
추 212
 
6.2%
동 197
 
5.8%
천 194
 
5.7%
시 192
 
5.6%
역 191
 
5.6%
구 191
 
5.6%
광 190
 
5.6%
Other values (134) 1347
39.6%
Decimal Number
ValueCountFrequency (%)
1 210
26.6%
2 95
12.0%
3 94
11.9%
0 72
 
9.1%
4 68
 
8.6%
6 62
 
7.9%
5 55
 
7.0%
7 51
 
6.5%
9 41
 
5.2%
8 41
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
16.7%
P 1
16.7%
I 1
16.7%
N 1
16.7%
E 1
16.7%
C 1
16.7%
Space Separator
ValueCountFrequency (%)
929
100.0%
Open Punctuation
ValueCountFrequency (%)
( 192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Other Punctuation
ValueCountFrequency (%)
, 108
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3399
60.3%
Common 2231
39.6%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 253
 
7.4%
홀 217
 
6.4%
미 215
 
6.3%
추 212
 
6.2%
동 197
 
5.8%
천 194
 
5.7%
시 192
 
5.6%
역 191
 
5.6%
구 191
 
5.6%
광 190
 
5.6%
Other values (134) 1347
39.6%
Common
ValueCountFrequency (%)
929
41.6%
1 210
 
9.4%
( 192
 
8.6%
) 192
 
8.6%
, 108
 
4.8%
2 95
 
4.3%
3 94
 
4.2%
0 72
 
3.2%
4 68
 
3.0%
6 62
 
2.8%
Other values (5) 209
 
9.4%
Latin
ValueCountFrequency (%)
A 1
16.7%
P 1
16.7%
I 1
16.7%
N 1
16.7%
E 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3399
60.3%
ASCII 2237
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
929
41.5%
1 210
 
9.4%
( 192
 
8.6%
) 192
 
8.6%
, 108
 
4.8%
2 95
 
4.2%
3 94
 
4.2%
0 72
 
3.2%
4 68
 
3.0%
6 62
 
2.8%
Other values (11) 215
 
9.6%
Hangul
ValueCountFrequency (%)
인 253
 
7.4%
홀 217
 
6.4%
미 215
 
6.3%
추 212
 
6.2%
동 197
 
5.8%
천 194
 
5.7%
시 192
 
5.6%
역 191
 
5.6%
구 191
 
5.6%
광 190
 
5.6%
Other values (134) 1347
39.6%

전화번호
Text

MISSING 

Distinct186
Distinct (%)100.0%
Missing4
Missing (%)2.1%
Memory size1.6 KiB
2024-03-18T12:20:05.827013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016129
Min length12

Characters and Unicode

Total characters2235
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

Unique186 ?
Unique (%)100.0%

Sample

1st row032-424-6027
2nd row070-8820-8881
3rd row032-432-3144
4th row032-423-4421
5th row032-432-3505
ValueCountFrequency (%)
032-872-2201 1
 
0.5%
032-884-5848 1
 
0.5%
032-439-5913 1
 
0.5%
032-873-9965 1
 
0.5%
032-882-8899 1
 
0.5%
032-888-8876 1
 
0.5%
032-862-8676 1
 
0.5%
032-425-2958 1
 
0.5%
032-883-2038 1
 
0.5%
032-863-3900 1
 
0.5%
Other values (176) 176
94.6%
2024-03-18T12:20:06.123204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 372
16.6%
2 320
14.3%
3 292
13.1%
0 288
12.9%
8 273
12.2%
7 135
 
6.0%
4 123
 
5.5%
5 122
 
5.5%
6 115
 
5.1%
1 108
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1863
83.4%
Dash Punctuation 372
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 320
17.2%
3 292
15.7%
0 288
15.5%
8 273
14.7%
7 135
7.2%
4 123
 
6.6%
5 122
 
6.5%
6 115
 
6.2%
1 108
 
5.8%
9 87
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2235
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 372
16.6%
2 320
14.3%
3 292
13.1%
0 288
12.9%
8 273
12.2%
7 135
 
6.0%
4 123
 
5.5%
5 122
 
5.5%
6 115
 
5.1%
1 108
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2235
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 372
16.6%
2 320
14.3%
3 292
13.1%
0 288
12.9%
8 273
12.2%
7 135
 
6.0%
4 123
 
5.5%
5 122
 
5.5%
6 115
 
5.1%
1 108
 
4.8%

지번주소
Text

MISSING 

Distinct173
Distinct (%)98.3%
Missing14
Missing (%)7.4%
Memory size1.6 KiB
2024-03-18T12:20:06.336113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length24.948864
Min length16

Characters and Unicode

Total characters4391
Distinct characters151
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

Unique172 ?
Unique (%)97.7%

Sample

1st row인천광역시 미추홀구 용현동 191-4
2nd row인천광역시 미추홀구 주안동 0
3rd row인천광역시 미추홀구 주안동 0
4th row인천광역시 미추홀구 학익동 420-18
5th row인천광역시 미추홀구 주안동 0
ValueCountFrequency (%)
인천광역시 176
21.5%
미추홀구 176
21.5%
주안동 49
 
6.0%
용현동 35
 
4.3%
숭의동 15
 
1.8%
1층 14
 
1.7%
학익동 13
 
1.6%
도화동 11
 
1.3%
주안1동 8
 
1.0%
주안5동 6
 
0.7%
Other values (269) 317
38.7%
2024-03-18T12:20:06.691289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
689
 
15.7%
1 222
 
5.1%
인 183
 
4.2%
동 182
 
4.1%
천 181
 
4.1%
미 180
 
4.1%
시 178
 
4.1%
역 177
 
4.0%
추 177
 
4.0%
홀 177
 
4.0%
Other values (141) 2045
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2642
60.2%
Decimal Number 910
 
20.7%
Space Separator 689
 
15.7%
Dash Punctuation 130
 
3.0%
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 (%)
인 183
 
6.9%
동 182
 
6.9%
천 181
 
6.9%
미 180
 
6.8%
시 178
 
6.7%
역 177
 
6.7%
추 177
 
6.7%
홀 177
 
6.7%
광 176
 
6.7%
구 176
 
6.7%
Other values (118) 855
32.4%
Decimal Number
ValueCountFrequency (%)
1 222
24.4%
2 112
12.3%
4 91
10.0%
6 86
 
9.5%
5 83
 
9.1%
3 82
 
9.0%
0 75
 
8.2%
7 61
 
6.7%
9 50
 
5.5%
8 48
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
P 2
22.2%
A 1
11.1%
N 1
11.1%
E 1
11.1%
V 1
11.1%
C 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2642
60.2%
Common 1740
39.6%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 183
 
6.9%
동 182
 
6.9%
천 181
 
6.9%
미 180
 
6.8%
시 178
 
6.7%
역 177
 
6.7%
추 177
 
6.7%
홀 177
 
6.7%
광 176
 
6.7%
구 176
 
6.7%
Other values (118) 855
32.4%
Common
ValueCountFrequency (%)
689
39.6%
1 222
 
12.8%
- 130
 
7.5%
2 112
 
6.4%
4 91
 
5.2%
6 86
 
4.9%
5 83
 
4.8%
3 82
 
4.7%
0 75
 
4.3%
7 61
 
3.5%
Other values (6) 109
 
6.3%
Latin
ValueCountFrequency (%)
I 2
22.2%
P 2
22.2%
A 1
11.1%
N 1
11.1%
E 1
11.1%
V 1
11.1%
C 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2642
60.2%
ASCII 1749
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
689
39.4%
1 222
 
12.7%
- 130
 
7.4%
2 112
 
6.4%
4 91
 
5.2%
6 86
 
4.9%
5 83
 
4.7%
3 82
 
4.7%
0 75
 
4.3%
7 61
 
3.5%
Other values (13) 118
 
6.7%
Hangul
ValueCountFrequency (%)
인 183
 
6.9%
동 182
 
6.9%
천 181
 
6.9%
미 180
 
6.8%
시 178
 
6.7%
역 177
 
6.7%
추 177
 
6.7%
홀 177
 
6.7%
광 176
 
6.7%
구 176
 
6.7%
Other values (118) 855
32.4%

위도
Real number (ℝ)

Distinct181
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455675
Minimum37.437384
Maximum37.477956
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-18T12:20:06.829322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437384
5-th percentile37.442055
Q137.45
median37.457296
Q337.461196
95-th percentile37.467923
Maximum37.477956
Range0.0405717
Interquartile range (IQR)0.011195713

Descriptive statistics

Standard deviation0.0081271273
Coefficient of variation (CV)0.00021697986
Kurtosis-0.3834615
Mean37.455675
Median Absolute Deviation (MAD)0.0058089
Skewness-0.087176744
Sum7116.5783
Variance6.6050198 × 10-5
MonotonicityNot monotonic
2024-03-18T12:20:06.991551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4580182 4
 
2.1%
37.46167352 2
 
1.1%
37.44999319 2
 
1.1%
37.44756126 2
 
1.1%
37.4610162 2
 
1.1%
37.46039207 2
 
1.1%
37.44250623 2
 
1.1%
37.45720813 1
 
0.5%
37.46718079 1
 
0.5%
37.45749196 1
 
0.5%
Other values (171) 171
90.0%
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%
37.43953362 1
0.5%
37.44042158 1
0.5%
37.4414509 1
0.5%
37.44184925 1
0.5%
37.44195578 1
0.5%
ValueCountFrequency (%)
37.47795559 1
0.5%
37.47685805 1
0.5%
37.47211604 1
0.5%
37.46991797 1
0.5%
37.4694746 1
0.5%
37.46892673 1
0.5%
37.46857416 1
0.5%
37.46835781 1
0.5%
37.46807119 1
0.5%
37.4679645 1
0.5%

경도
Real number (ℝ)

Distinct181
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66703
Minimum126.63327
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-18T12:20:07.131131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63327
5-th percentile126.63739
Q1126.65147
median126.67158
Q3126.68059
95-th percentile126.68984
Maximum126.70152
Range0.0682483
Interquartile range (IQR)0.02911845

Descriptive statistics

Standard deviation0.017728563
Coefficient of variation (CV)0.00013996194
Kurtosis-1.0564276
Mean126.66703
Median Absolute Deviation (MAD)0.01201755
Skewness-0.34109919
Sum24066.735
Variance0.00031430193
MonotonicityNot monotonic
2024-03-18T12:20:07.307755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.6811632 4
 
2.1%
126.6433975 2
 
1.1%
126.6336714 2
 
1.1%
126.6810299 2
 
1.1%
126.6735675 2
 
1.1%
126.6891379 2
 
1.1%
126.7015187 2
 
1.1%
126.6500013 1
 
0.5%
126.678787 1
 
0.5%
126.6839613 1
 
0.5%
Other values (171) 171
90.0%
ValueCountFrequency (%)
126.6332704 1
0.5%
126.6336714 2
1.1%
126.635584 1
0.5%
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%
ValueCountFrequency (%)
126.7015187 2
1.1%
126.6969867 1
0.5%
126.6952992 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

2024-03-18T12:20:03.766442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.036427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.527828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.842194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.119180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.612731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.916504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.210930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:20:03.691669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:20:07.422466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.2670.000
위도0.2671.0000.788
경도0.0000.7881.000
2024-03-18T12:20:07.526292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.0320.039
위도0.0321.0000.035
경도0.0390.0351.000

Missing values

2024-03-18T12:20:04.011189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:20:04.100425image/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.
2024-03-18T12:20:04.170295image/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
01인하후문약국인천광역시 미추홀구 인하로 73-1, 1층 우측 (용현동)<NA>인천광역시 미추홀구 용현동 191-437.451423126.656598
12뉴아인약국인천광역시 미추홀구 경인로 372, 1014호 (주안동)032-424-6027인천광역시 미추홀구 주안동 037.458018126.681163
23코뿔소약국인천광역시 미추홀구 경인로 372, 1018호 (주안동)070-8820-8881인천광역시 미추홀구 주안동 037.458018126.681163
34동신온누리약국인천광역시 미추홀구 소성로 93, 1층 (학익동)032-432-3144인천광역시 미추홀구 학익동 420-1837.445053126.659512
45아이사랑약국인천광역시 미추홀구 경인로 372, 1011호 (주안동, 포레나 미추홀)032-423-4421인천광역시 미추홀구 주안동 037.458018126.681163
56애비뉴퍼스트약국인천광역시 미추홀구 경인로 372, 1012호 (주안동, 포레나 미추홀)032-432-3505인천광역시 미추홀구 주안동 037.458018126.681163
67건강온누리약국인천광역시 미추홀구 아암대로 15, 104호 (용현동)032-201-7500인천광역시 미추홀구 용현동 573-737.459356126.637908
78제일건강약국인천광역시 미추홀구 경인로 291, 1층 (도화동)032-873-7776인천광역시 미추홀구 도화동 391-1337.461016126.673568
89주안약국인천광역시 미추홀구 미추홀대로 704, 1층 (주안동)032-422-4279인천광역시 미추홀구 주안동 174-437.460144126.680413
910숭의로터리약국인천광역시 미추홀구 석정로 21, 103호 일부, 104호 (숭의동)032-887-8001인천광역시 미추홀구 숭의동 342-537.46174126.642049
연번약국명칭도로명주소전화번호지번주소위도경도
180181한신약국인천광역시 미추홀구 경원대로 717 (주안동)032-422-9578인천광역시 미추홀구 주안동 1621번지 인천관교한신휴플러스상가에이동 107호37.447083126.685205
181182한아름약국인천광역시 미추홀구 경원대로 869 (주안동, 르네상스빌딩)032-420-1245<NA>37.460392126.689138
182183햇님약국인천광역시 미추홀구 숙골로 114, 우리타워 103호 (도화동)032-872-2582인천광역시 미추홀구 도화동 1005번지 6호 우리타워37.472116126.662017
183184행복약국인천광역시 미추홀구 한나루로 589, 102호 (도화동)032-861-9991인천광역시 미추홀구 도화동 441-24번지 102호37.458652126.67178
184185행복한약국인천광역시 미추홀구 미추홀대로722번길 6 (주안동)032-421-3868인천광역시 미추홀구 주안1동 161-2 지상1층 일부37.46166126.680617
185186현대메디칼약국인천광역시 미추홀구 낙섬서로 4 (용현동)032-889-1891인천광역시 미추홀구 용현5동 627-287 현대메디칼센터 103호37.449993126.633671
186187혜은약국인천광역시 미추홀구 인하로262번길 6, 1층 (주안동)032-872-8101인천광역시 미추홀구 주안동 1330-3번지37.447915126.677144
187188화생당약국인천광역시 미추홀구 길파로 30 (주안동)032-866-1892인천광역시 미추홀구 주안동 16-69번지37.468358126.679865
188189휴베이스센트럴약국인천광역시 미추홀구 연남로 35, 인천종합터미널,롯데백화점 지하1층 (관교동)<NA>인천광역시 미추홀구 관교동 15 인천종합터미널,롯데백화점37.442506126.701519
189190희망약국인천광역시 미추홀구 미추홀대로 573, 1층 (주안동)032-876-3700<NA>37.448531126.679311