Overview

Dataset statistics

Number of variables9
Number of observations184
Missing cells11
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.6 KiB
Average record size in memory75.7 B

Variable types

Numeric3
Text3
Categorical3

Dataset

Description대구광역시 동구 약국현황 대구 동구 소재의 약국 현황 데이터입니다. 이 데이터는 약국명칭, 약국 소재지, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15062095/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 행정동명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동명 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
법정동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
약국전화번호 has 11 (6.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:16:18.071316
Analysis finished2023-12-12 23:16:19.572721
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.5
Minimum1
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T08:16:19.640108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.15
Q146.75
median92.5
Q3138.25
95-th percentile174.85
Maximum184
Range183
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation53.260367
Coefficient of variation (CV)0.57578775
Kurtosis-1.2
Mean92.5
Median Absolute Deviation (MAD)46
Skewness0
Sum17020
Variance2836.6667
MonotonicityStrictly increasing
2023-12-13T08:16:19.772308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
128 1
 
0.5%
119 1
 
0.5%
120 1
 
0.5%
121 1
 
0.5%
122 1
 
0.5%
123 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
Other values (174) 174
94.6%
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 (%)
184 1
0.5%
183 1
0.5%
182 1
0.5%
181 1
0.5%
180 1
0.5%
179 1
0.5%
178 1
0.5%
177 1
0.5%
176 1
0.5%
175 1
0.5%

약국명칭
Text

Distinct181
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:16:20.050064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.6576087
Min length3

Characters and Unicode

Total characters857
Distinct characters161
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)96.7%

Sample

1st row드림약국
2nd row은행약국
3rd row신천다정약국
4th row자이약국
5th row맑은샘약국
ValueCountFrequency (%)
약국 3
 
1.6%
양춘당약국 2
 
1.1%
예약국 2
 
1.1%
율하우리들약국 2
 
1.1%
미래약국 2
 
1.1%
드림약국 1
 
0.5%
희망약국 1
 
0.5%
농심약국 1
 
0.5%
효성약국 1
 
0.5%
정인약국 1
 
0.5%
Other values (173) 173
91.5%
2023-12-13T08:16:20.437187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 185
21.6%
국 185
21.6%
리 16
 
1.9%
한 14
 
1.6%
새 11
 
1.3%
하 11
 
1.3%
온 11
 
1.3%
신 10
 
1.2%
누 10
 
1.2%
성 10
 
1.2%
Other values (151) 394
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 852
99.4%
Space Separator 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 185
21.7%
국 185
21.7%
리 16
 
1.9%
한 14
 
1.6%
새 11
 
1.3%
하 11
 
1.3%
온 11
 
1.3%
신 10
 
1.2%
누 10
 
1.2%
성 10
 
1.2%
Other values (150) 389
45.7%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 852
99.4%
Common 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 185
21.7%
국 185
21.7%
리 16
 
1.9%
한 14
 
1.6%
새 11
 
1.3%
하 11
 
1.3%
온 11
 
1.3%
신 10
 
1.2%
누 10
 
1.2%
성 10
 
1.2%
Other values (150) 389
45.7%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 852
99.4%
ASCII 5
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 185
21.7%
국 185
21.7%
리 16
 
1.9%
한 14
 
1.6%
새 11
 
1.3%
하 11
 
1.3%
온 11
 
1.3%
신 10
 
1.2%
누 10
 
1.2%
성 10
 
1.2%
Other values (150) 389
45.7%
ASCII
ValueCountFrequency (%)
5
100.0%

약국소재지(도로명)
Text

Distinct181
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T08:16:20.687940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length26.820652
Min length20

Characters and Unicode

Total characters4935
Distinct characters148
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

Unique178 ?
Unique (%)96.7%

Sample

1st row대구광역시 동구 아양로 162, 1층 (신암동)
2nd row대구광역시 동구 동촌로 229, 1층 (방촌동)
3rd row대구광역시 동구 장등로 56, 100,101호 (신천동, 벽산e-솔렌스힐)
4th row대구광역시 동구 송라로10길 33, 상가 302동 2105호 (신천동, 동대구역 센트럴시티자이)
5th row대구광역시 동구 신암남로 180(신암동)
ValueCountFrequency (%)
대구광역시 184
17.1%
동구 184
17.1%
1층 85
 
7.9%
신암동 40
 
3.7%
아양로 31
 
2.9%
신천동 26
 
2.4%
동촌로 23
 
2.1%
방촌동 22
 
2.0%
효목동 19
 
1.8%
율하동 17
 
1.6%
Other values (256) 445
41.4%
2023-12-13T08:16:21.381481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
892
18.1%
동 439
 
8.9%
구 374
 
7.6%
1 244
 
4.9%
대 194
 
3.9%
로 191
 
3.9%
역 187
 
3.8%
시 187
 
3.8%
) 184
 
3.7%
광 184
 
3.7%
Other values (138) 1859
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2799
56.7%
Space Separator 892
 
18.1%
Decimal Number 723
 
14.7%
Close Punctuation 184
 
3.7%
Open Punctuation 184
 
3.7%
Other Punctuation 131
 
2.7%
Dash Punctuation 18
 
0.4%
Uppercase Letter 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 439
15.7%
구 374
13.4%
대 194
 
6.9%
로 191
 
6.8%
역 187
 
6.7%
시 187
 
6.7%
광 184
 
6.6%
신 104
 
3.7%
층 97
 
3.5%
암 54
 
1.9%
Other values (119) 788
28.2%
Decimal Number
ValueCountFrequency (%)
1 244
33.7%
2 99
13.7%
0 73
 
10.1%
3 59
 
8.2%
5 52
 
7.2%
8 51
 
7.1%
4 42
 
5.8%
9 35
 
4.8%
7 34
 
4.7%
6 34
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
G 1
33.3%
H 1
33.3%
Space Separator
ValueCountFrequency (%)
892
100.0%
Close Punctuation
ValueCountFrequency (%)
) 184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 184
100.0%
Other Punctuation
ValueCountFrequency (%)
, 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2799
56.7%
Common 2132
43.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 439
15.7%
구 374
13.4%
대 194
 
6.9%
로 191
 
6.8%
역 187
 
6.7%
시 187
 
6.7%
광 184
 
6.6%
신 104
 
3.7%
층 97
 
3.5%
암 54
 
1.9%
Other values (119) 788
28.2%
Common
ValueCountFrequency (%)
892
41.8%
1 244
 
11.4%
) 184
 
8.6%
( 184
 
8.6%
, 131
 
6.1%
2 99
 
4.6%
0 73
 
3.4%
3 59
 
2.8%
5 52
 
2.4%
8 51
 
2.4%
Other values (5) 163
 
7.6%
Latin
ValueCountFrequency (%)
A 1
25.0%
e 1
25.0%
G 1
25.0%
H 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2799
56.7%
ASCII 2136
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
892
41.8%
1 244
 
11.4%
) 184
 
8.6%
( 184
 
8.6%
, 131
 
6.1%
2 99
 
4.6%
0 73
 
3.4%
3 59
 
2.8%
5 52
 
2.4%
8 51
 
2.4%
Other values (9) 167
 
7.8%
Hangul
ValueCountFrequency (%)
동 439
15.7%
구 374
13.4%
대 194
 
6.9%
로 191
 
6.8%
역 187
 
6.7%
시 187
 
6.7%
광 184
 
6.6%
신 104
 
3.7%
층 97
 
3.5%
암 54
 
1.9%
Other values (119) 788
28.2%

약국전화번호
Text

MISSING 

Distinct170
Distinct (%)98.3%
Missing11
Missing (%)6.0%
Memory size1.6 KiB
2023-12-13T08:16:21.655267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.00578
Min length12

Characters and Unicode

Total characters2077
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

Unique167 ?
Unique (%)96.5%

Sample

1st row053-982-3535
2nd row053-242-3691
3rd row053-751-9005
4th row053-939-0911
5th row053-965-7233
ValueCountFrequency (%)
053-982-6900 2
 
1.2%
053-965-6006 2
 
1.2%
053-941-3535 2
 
1.2%
053-754-2783 1
 
0.6%
053-965-4119 1
 
0.6%
053-964-2584 1
 
0.6%
053-965-5360 1
 
0.6%
053-957-5606 1
 
0.6%
053-752-2335 1
 
0.6%
053-965-6574 1
 
0.6%
Other values (160) 160
92.5%
2023-12-13T08:16:22.028920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 346
16.7%
5 325
15.6%
0 287
13.8%
3 266
12.8%
9 178
8.6%
2 136
 
6.5%
6 123
 
5.9%
1 123
 
5.9%
8 103
 
5.0%
4 98
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1731
83.3%
Dash Punctuation 346
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 325
18.8%
0 287
16.6%
3 266
15.4%
9 178
10.3%
2 136
7.9%
6 123
 
7.1%
1 123
 
7.1%
8 103
 
6.0%
4 98
 
5.7%
7 92
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 346
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 346
16.7%
5 325
15.6%
0 287
13.8%
3 266
12.8%
9 178
8.6%
2 136
 
6.5%
6 123
 
5.9%
1 123
 
5.9%
8 103
 
5.0%
4 98
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 346
16.7%
5 325
15.6%
0 287
13.8%
3 266
12.8%
9 178
8.6%
2 136
 
6.5%
6 123
 
5.9%
1 123
 
5.9%
8 103
 
5.0%
4 98
 
4.7%

행정동명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
안심1동
24 
신천1.2동
12 
방촌동
12 
불로.봉무동
12 
신암4동
12 
Other values (16)
112 

Length

Max length6
Median length4
Mean length4.0434783
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row신암4동
2nd row해안동
3rd row신천3동
4th row신천3동
5th row신암4동

Common Values

ValueCountFrequency (%)
안심1동 24
 
13.0%
신천1.2동 12
 
6.5%
방촌동 12
 
6.5%
불로.봉무동 12
 
6.5%
신암4동 12
 
6.5%
신암1동 11
 
6.0%
안심4동 11
 
6.0%
신천3동 10
 
5.4%
효목2동 10
 
5.4%
해안동 10
 
5.4%
Other values (11) 60
32.6%

Length

2023-12-13T08:16:22.195178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안심1동 24
 
13.0%
방촌동 12
 
6.5%
불로.봉무동 12
 
6.5%
신암4동 12
 
6.5%
신천1.2동 12
 
6.5%
신암1동 11
 
6.0%
안심4동 11
 
6.0%
신천3동 10
 
5.4%
효목2동 10
 
5.4%
해안동 10
 
5.4%
Other values (11) 60
32.6%

법정동명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
신암동
43 
신천동
26 
방촌동
22 
효목동
19 
율하동
17 
Other values (13)
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st row신암동
2nd row방촌동
3rd row신천동
4th row신천동
5th row신암동

Common Values

ValueCountFrequency (%)
신암동 43
23.4%
신천동 26
14.1%
방촌동 22
12.0%
효목동 19
10.3%
율하동 17
 
9.2%
신서동 12
 
6.5%
신기동 7
 
3.8%
불로동 7
 
3.8%
지저동 6
 
3.3%
봉무동 5
 
2.7%
Other values (8) 20
10.9%

Length

2023-12-13T08:16:22.300649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신암동 43
23.4%
신천동 26
14.1%
방촌동 22
12.0%
효목동 19
10.3%
율하동 17
 
9.2%
신서동 12
 
6.5%
신기동 7
 
3.8%
불로동 7
 
3.8%
지저동 6
 
3.3%
봉무동 5
 
2.7%
Other values (8) 20
10.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct177
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.881121
Minimum35.863107
Maximum35.942828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T08:16:22.409623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.863107
5-th percentile35.866332
Q135.87177
median35.879368
Q335.883578
95-th percentile35.913724
Maximum35.942828
Range0.07972056
Interquartile range (IQR)0.011807955

Descriptive statistics

Standard deviation0.015195412
Coefficient of variation (CV)0.00042349322
Kurtosis4.8642434
Mean35.881121
Median Absolute Deviation (MAD)0.00634244
Skewness2.0603217
Sum6602.1263
Variance0.00023090053
MonotonicityNot monotonic
2023-12-13T08:16:22.535874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8812778 2
 
1.1%
35.86635582 2
 
1.1%
35.86840109 2
 
1.1%
35.87357663 2
 
1.1%
35.88242302 2
 
1.1%
35.88335295 2
 
1.1%
35.8702668 2
 
1.1%
35.91186278 1
 
0.5%
35.86974559 1
 
0.5%
35.88440181 1
 
0.5%
Other values (167) 167
90.8%
ValueCountFrequency (%)
35.86310741 1
0.5%
35.86315576 1
0.5%
35.86326046 1
0.5%
35.86332649 1
0.5%
35.86341152 1
0.5%
35.86351721 1
0.5%
35.86358508 1
0.5%
35.86435602 1
0.5%
35.86621757 1
0.5%
35.86632754 1
0.5%
ValueCountFrequency (%)
35.94282797 1
0.5%
35.94090409 1
0.5%
35.9403159 1
0.5%
35.94008648 1
0.5%
35.92286228 1
0.5%
35.92284521 1
0.5%
35.92246193 1
0.5%
35.92204155 1
0.5%
35.92091144 1
0.5%
35.91395386 1
0.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct177
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65515
Minimum128.60945
Maximum128.74958
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T08:16:22.658675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.60945
5-th percentile128.61513
Q1128.62429
median128.6396
Q3128.69228
95-th percentile128.72506
Maximum128.74958
Range0.1401316
Interquartile range (IQR)0.067987325

Descriptive statistics

Standard deviation0.037435236
Coefficient of variation (CV)0.00029097347
Kurtosis-0.71789726
Mean128.65515
Median Absolute Deviation (MAD)0.021216
Skewness0.77907755
Sum23672.548
Variance0.0014013969
MonotonicityNot monotonic
2023-12-13T08:16:22.786165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6651135 2
 
1.1%
128.7250821 2
 
1.1%
128.624311 2
 
1.1%
128.6152155 2
 
1.1%
128.6196035 2
 
1.1%
128.6227783 2
 
1.1%
128.6916423 2
 
1.1%
128.6413498 1
 
0.5%
128.7068307 1
 
0.5%
128.6255998 1
 
0.5%
Other values (167) 167
90.8%
ValueCountFrequency (%)
128.6094487 1
0.5%
128.6107646 1
0.5%
128.610977 1
0.5%
128.6119275 1
0.5%
128.6119355 1
0.5%
128.6124671 1
0.5%
128.6135561 1
0.5%
128.6141719 1
0.5%
128.6148222 1
0.5%
128.6151099 1
0.5%
ValueCountFrequency (%)
128.7495803 1
0.5%
128.7493292 1
0.5%
128.7321779 1
0.5%
128.7296956 1
0.5%
128.7292747 1
0.5%
128.7274375 1
0.5%
128.7265698 1
0.5%
128.7255595 1
0.5%
128.7250821 2
1.1%
128.7249397 1
0.5%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-06-14
184 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-14
2nd row2023-06-14
3rd row2023-06-14
4th row2023-06-14
5th row2023-06-14

Common Values

ValueCountFrequency (%)
2023-06-14 184
100.0%

Length

2023-12-13T08:16:22.904188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:16:23.005481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-14 184
100.0%

Interactions

2023-12-13T08:16:19.081608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.509714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.780860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:19.167735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.599963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.866410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:19.258208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.697663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:16:18.989183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:16:23.069093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동명법정동명위도경도
순번1.0000.2280.3040.2650.202
행정동명0.2281.0000.9710.9450.934
법정동명0.3040.9711.0000.9670.945
위도0.2650.9450.9671.0000.623
경도0.2020.9340.9450.6231.000
2023-12-13T08:16:23.150901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명행정동명
법정동명1.0000.757
행정동명0.7571.000
2023-12-13T08:16:23.220343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도행정동명법정동명
순번1.0000.075-0.0380.0790.116
위도0.0751.000-0.3380.7500.837
경도-0.038-0.3381.0000.6840.742
행정동명0.0790.7500.6841.0000.757
법정동명0.1160.8370.7420.7571.000

Missing values

2023-12-13T08:16:19.378249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:16:19.523297image/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

순번약국명칭약국소재지(도로명)약국전화번호행정동명법정동명위도경도데이터기준일
01드림약국대구광역시 동구 아양로 162, 1층 (신암동)<NA>신암4동신암동35.885321128.6308572023-06-14
12은행약국대구광역시 동구 동촌로 229, 1층 (방촌동)053-982-3535해안동방촌동35.881626128.6656592023-06-14
23신천다정약국대구광역시 동구 장등로 56, 100,101호 (신천동, 벽산e-솔렌스힐)053-242-3691신천3동신천동35.872412128.6242322023-06-14
34자이약국대구광역시 동구 송라로10길 33, 상가 302동 2105호 (신천동, 동대구역 센트럴시티자이)053-751-9005신천3동신천동35.873488128.6237092023-06-14
45맑은샘약국대구광역시 동구 신암남로 180(신암동)053-939-0911신암4동신암동35.884805128.6330132023-06-14
56우리제일약국대구광역시 동구 국채보상로 791, 성암빌딩 1층 (신천동)<NA>신천1.2동신천동35.868203128.6173442023-06-14
67엘약국대구광역시 동구 안심로 368, 1층 (신서동)053-965-7233안심3동신서동35.867873128.7246092023-06-14
78새평화약국대구광역시 동구 아양로15길 2(신암동)053-942-8185신암4동신암동35.883495128.6231012023-06-14
89스마일약국대구광역시 동구 안심로 389, 비에스메디타워 106호 (신서동)053-219-8823안심4동신서동35.869204128.726572023-06-14
910미소약국대구광역시 동구 효목로 41, 1층 (효목동)053-755-2468효목2동효목동35.877172128.6394412023-06-14
순번약국명칭약국소재지(도로명)약국전화번호행정동명법정동명위도경도데이터기준일
174175명인약국대구광역시 동구 동촌로 45 (입석동)053-982-1029동촌동입석동35.889935128.6478522023-06-14
175176강남약국대구광역시 동구 신암로 98 (신암동)053-941-1543신암2동신암동35.879449128.6107652023-06-14
176177행복약국대구광역시 동구 동대구로85길 27 (신천동)053-754-6261신천3동신천동35.872808128.624392023-06-14
177178대원약국대구광역시 동구 안심로49길 110 (서호동)053-962-2975안심4동서호동35.870795128.7108152023-06-14
178179허약국대구광역시 동구 동촌로 212 (방촌동)053-982-5837방촌동방촌동35.882107128.6634042023-06-14
179180영생약국대구광역시 동구 아양로8길 13 (신암동)053-941-2972신암3동신암동35.88073128.6193912023-06-14
180181새동보약국대구광역시 동구 신암남로27길 81 (신암동)053-941-0427신암4동신암동35.883824128.6308782023-06-14
181182화신약국대구광역시 동구 효신로 24 (효목동)053-754-2783효목2동효목동35.874169128.6347112023-06-14
182183삼강약국대구광역시 동구 신암남로 20 (신암동)053-941-3356신암3동신암동35.877762128.6181052023-06-14
183184보민약국대구광역시 동구 동부로 8-1 (신천동)053-426-0615신천1.2동신천동35.873801128.6135562023-06-14