Overview

Dataset statistics

Number of variables5
Number of observations252
Missing cells14
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory42.5 B

Variable types

Numeric2
Text3

Dataset

Description부평구 약국 현황(순번 ,약국명칭,소재지,약국전화번호)예)2,착한약국,인천광역시 부평구 길주남로 157, 태성프라자 101호 (부개동),070-7788-7582
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3045123&srcSe=7661IVAWM27C61E190

Alerts

전화번호 has 14 (5.6%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 16:46:38.819989
Analysis finished2024-04-20 16:46:41.788730
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct252
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.5
Minimum1
Maximum252
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-21T01:46:42.018735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.55
Q163.75
median126.5
Q3189.25
95-th percentile239.45
Maximum252
Range251
Interquartile range (IQR)125.5

Descriptive statistics

Standard deviation72.890329
Coefficient of variation (CV)0.57620813
Kurtosis-1.2
Mean126.5
Median Absolute Deviation (MAD)63
Skewness0
Sum31878
Variance5313
MonotonicityStrictly increasing
2024-04-21T01:46:42.308873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
175 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
Other values (242) 242
96.0%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%

약국명칭
Text

Distinct246
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-21T01:46:43.365418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.0912698
Min length3

Characters and Unicode

Total characters1283
Distinct characters201
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)95.2%

Sample

1st row부평 해약국
2nd row롯데약국
3rd row동암가장큰약국
4th row밝은약국
5th row365그랜드온누리약국
ValueCountFrequency (%)
엘림약국 2
 
0.8%
현대메디칼약국 2
 
0.8%
수보당약국 2
 
0.8%
신생약국 2
 
0.8%
노벨약국 2
 
0.8%
경인약국 2
 
0.8%
부평온누리약국 1
 
0.4%
드림약국 1
 
0.4%
희망약국 1
 
0.4%
예스약국 1
 
0.4%
Other values (238) 238
93.7%
2024-04-21T01:46:44.653928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
약 252
19.6%
국 252
19.6%
부 31
 
2.4%
평 26
 
2.0%
리 25
 
1.9%
한 24
 
1.9%
온 18
 
1.4%
누 17
 
1.3%
동 14
 
1.1%
나 13
 
1.0%
Other values (191) 611
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1266
98.7%
Decimal Number 15
 
1.2%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
약 252
19.9%
국 252
19.9%
부 31
 
2.4%
평 26
 
2.1%
리 25
 
2.0%
한 24
 
1.9%
온 18
 
1.4%
누 17
 
1.3%
동 14
 
1.1%
나 13
 
1.0%
Other values (184) 594
46.9%
Decimal Number
ValueCountFrequency (%)
3 4
26.7%
6 4
26.7%
5 4
26.7%
2 1
 
6.7%
1 1
 
6.7%
4 1
 
6.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1266
98.7%
Common 17
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
약 252
19.9%
국 252
19.9%
부 31
 
2.4%
평 26
 
2.1%
리 25
 
2.0%
한 24
 
1.9%
온 18
 
1.4%
누 17
 
1.3%
동 14
 
1.1%
나 13
 
1.0%
Other values (184) 594
46.9%
Common
ValueCountFrequency (%)
3 4
23.5%
6 4
23.5%
5 4
23.5%
2
11.8%
2 1
 
5.9%
1 1
 
5.9%
4 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1266
98.7%
ASCII 17
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
약 252
19.9%
국 252
19.9%
부 31
 
2.4%
평 26
 
2.1%
리 25
 
2.0%
한 24
 
1.9%
온 18
 
1.4%
누 17
 
1.3%
동 14
 
1.1%
나 13
 
1.0%
Other values (184) 594
46.9%
ASCII
ValueCountFrequency (%)
3 4
23.5%
6 4
23.5%
5 4
23.5%
2
11.8%
2 1
 
5.9%
1 1
 
5.9%
4 1
 
5.9%

소재지(도로명)
Text

Distinct244
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-04-21T01:46:45.630553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length42
Mean length30.47619
Min length20

Characters and Unicode

Total characters7680
Distinct characters211
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)93.7%

Sample

1st row인천광역시 부평구 산청로 97, 단지내상가 4동 1층 403,404호 (청천동, e편한세상부평그랑힐스)
2nd row인천광역시 부평구 길주로 623, 대덕리치아노 3층 331호 (삼산동)
3rd row인천광역시 부평구 열우물로 66, 해동빌딩 1층 일부호 (십정동)
4th row인천광역시 부평구 경원대로 1373, 북인천우체국 1층 일부호 (부평동)
5th row인천광역시 부평구 마장로 314, 성수빌딩 101호 (산곡동)
ValueCountFrequency (%)
인천광역시 252
 
16.4%
부평구 252
 
16.4%
부평동 105
 
6.8%
1층 57
 
3.7%
산곡동 39
 
2.5%
부개동 28
 
1.8%
부평대로 24
 
1.6%
삼산동 24
 
1.6%
청천동 22
 
1.4%
십정동 20
 
1.3%
Other values (394) 716
46.5%
2024-04-21T01:46:47.227397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1287
 
16.8%
부 492
 
6.4%
평 413
 
5.4%
1 336
 
4.4%
동 287
 
3.7%
천 283
 
3.7%
인 268
 
3.5%
시 261
 
3.4%
광 260
 
3.4%
역 255
 
3.3%
Other values (201) 3538
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4490
58.5%
Space Separator 1287
 
16.8%
Decimal Number 1149
 
15.0%
Close Punctuation 253
 
3.3%
Open Punctuation 253
 
3.3%
Other Punctuation 206
 
2.7%
Dash Punctuation 27
 
0.4%
Uppercase Letter 9
 
0.1%
Lowercase Letter 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 492
 
11.0%
평 413
 
9.2%
동 287
 
6.4%
천 283
 
6.3%
인 268
 
6.0%
시 261
 
5.8%
광 260
 
5.8%
역 255
 
5.7%
구 254
 
5.7%
로 252
 
5.6%
Other values (170) 1465
32.6%
Decimal Number
ValueCountFrequency (%)
1 336
29.2%
0 144
12.5%
2 131
 
11.4%
3 124
 
10.8%
4 122
 
10.6%
5 75
 
6.5%
6 67
 
5.8%
8 58
 
5.0%
7 52
 
4.5%
9 40
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
D 1
11.1%
Y 1
11.1%
F 1
11.1%
P 1
11.1%
A 1
11.1%
K 1
11.1%
I 1
11.1%
M 1
11.1%
R 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
y 1
20.0%
t 1
20.0%
i 1
20.0%
c 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 205
99.5%
· 1
 
0.5%
Space Separator
ValueCountFrequency (%)
1287
100.0%
Close Punctuation
ValueCountFrequency (%)
) 253
100.0%
Open Punctuation
ValueCountFrequency (%)
( 253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4490
58.5%
Common 3176
41.4%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 492
 
11.0%
평 413
 
9.2%
동 287
 
6.4%
천 283
 
6.3%
인 268
 
6.0%
시 261
 
5.8%
광 260
 
5.8%
역 255
 
5.7%
구 254
 
5.7%
로 252
 
5.6%
Other values (170) 1465
32.6%
Common
ValueCountFrequency (%)
1287
40.5%
1 336
 
10.6%
) 253
 
8.0%
( 253
 
8.0%
, 205
 
6.5%
0 144
 
4.5%
2 131
 
4.1%
3 124
 
3.9%
4 122
 
3.8%
5 75
 
2.4%
Other values (7) 246
 
7.7%
Latin
ValueCountFrequency (%)
D 1
 
7.1%
Y 1
 
7.1%
F 1
 
7.1%
e 1
 
7.1%
y 1
 
7.1%
P 1
 
7.1%
A 1
 
7.1%
K 1
 
7.1%
I 1
 
7.1%
t 1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4490
58.5%
ASCII 3189
41.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1287
40.4%
1 336
 
10.5%
) 253
 
7.9%
( 253
 
7.9%
, 205
 
6.4%
0 144
 
4.5%
2 131
 
4.1%
3 124
 
3.9%
4 122
 
3.8%
5 75
 
2.4%
Other values (20) 259
 
8.1%
Hangul
ValueCountFrequency (%)
부 492
 
11.0%
평 413
 
9.2%
동 287
 
6.4%
천 283
 
6.3%
인 268
 
6.0%
시 261
 
5.8%
광 260
 
5.8%
역 255
 
5.7%
구 254
 
5.7%
로 252
 
5.6%
Other values (170) 1465
32.6%
None
ValueCountFrequency (%)
· 1
100.0%

전화번호
Text

MISSING 

Distinct232
Distinct (%)97.5%
Missing14
Missing (%)5.6%
Memory size2.1 KiB
2024-04-21T01:46:48.159011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.995798
Min length11

Characters and Unicode

Total characters2855
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

Unique226 ?
Unique (%)95.0%

Sample

1st row032-501-0730
2nd row032-511-8878
3rd row032-423-8881
4th row032-501-8985
5th row032-515-5327
ValueCountFrequency (%)
032-330-7571 2
 
0.8%
032-517-1574 2
 
0.8%
032-503-5050 2
 
0.8%
032-511-3589 2
 
0.8%
032-518-5456 2
 
0.8%
032-523-2233 2
 
0.8%
032-511-1666 1
 
0.4%
032-522-4410 1
 
0.4%
032-506-1101 1
 
0.4%
032-524-5800 1
 
0.4%
Other values (222) 222
93.3%
2024-04-21T01:46:49.489075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 475
16.6%
0 469
16.4%
2 428
15.0%
3 407
14.3%
5 341
11.9%
1 175
 
6.1%
8 138
 
4.8%
7 129
 
4.5%
6 109
 
3.8%
4 106
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2380
83.4%
Dash Punctuation 475
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 469
19.7%
2 428
18.0%
3 407
17.1%
5 341
14.3%
1 175
 
7.4%
8 138
 
5.8%
7 129
 
5.4%
6 109
 
4.6%
4 106
 
4.5%
9 78
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 475
16.6%
0 469
16.4%
2 428
15.0%
3 407
14.3%
5 341
11.9%
1 175
 
6.1%
8 138
 
4.8%
7 129
 
4.5%
6 109
 
3.8%
4 106
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 475
16.6%
0 469
16.4%
2 428
15.0%
3 407
14.3%
5 341
11.9%
1 175
 
6.1%
8 138
 
4.8%
7 129
 
4.5%
6 109
 
3.8%
4 106
 
3.7%

약국우편번호
Real number (ℝ)

Distinct88
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21381.163
Minimum21303
Maximum21458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-21T01:46:49.896284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21303
5-th percentile21312
Q121355
median21389
Q321405
95-th percentile21445
Maximum21458
Range155
Interquartile range (IQR)50

Descriptive statistics

Standard deviation37.427557
Coefficient of variation (CV)0.0017504921
Kurtosis-0.56218589
Mean21381.163
Median Absolute Deviation (MAD)27
Skewness-0.16720087
Sum5388053
Variance1400.822
MonotonicityNot monotonic
2024-04-21T01:46:50.346955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21344 13
 
5.2%
21404 11
 
4.4%
21405 11
 
4.4%
21389 9
 
3.6%
21377 9
 
3.6%
21388 8
 
3.2%
21419 8
 
3.2%
21391 7
 
2.8%
21425 7
 
2.8%
21362 7
 
2.8%
Other values (78) 162
64.3%
ValueCountFrequency (%)
21303 1
 
0.4%
21304 1
 
0.4%
21305 1
 
0.4%
21307 1
 
0.4%
21309 2
 
0.8%
21311 3
1.2%
21312 5
2.0%
21314 1
 
0.4%
21315 1
 
0.4%
21316 1
 
0.4%
ValueCountFrequency (%)
21458 2
 
0.8%
21457 1
 
0.4%
21452 3
1.2%
21451 1
 
0.4%
21450 2
 
0.8%
21445 6
2.4%
21443 1
 
0.4%
21442 1
 
0.4%
21439 2
 
0.8%
21438 1
 
0.4%

Interactions

2024-04-21T01:46:40.746440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:46:40.240722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:46:40.999459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:46:40.480478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T01:46:50.621722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번약국우편번호
순번1.0000.000
약국우편번호0.0001.000
2024-04-21T01:46:50.842068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번약국우편번호
순번1.0000.001
약국우편번호0.0011.000

Missing values

2024-04-21T01:46:41.351392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T01:46:41.666311image/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

순번약국명칭소재지(도로명)전화번호약국우편번호
01부평 해약국인천광역시 부평구 산청로 97, 단지내상가 4동 1층 403,404호 (청천동, e편한세상부평그랑힐스)032-501-073021303
12롯데약국인천광역시 부평구 길주로 623, 대덕리치아노 3층 331호 (삼산동)032-511-887821344
23동암가장큰약국인천광역시 부평구 열우물로 66, 해동빌딩 1층 일부호 (십정동)032-423-888121445
34밝은약국인천광역시 부평구 경원대로 1373, 북인천우체국 1층 일부호 (부평동)032-501-898521389
45365그랜드온누리약국인천광역시 부평구 마장로 314, 성수빌딩 101호 (산곡동)<NA>21362
56청천약국인천광역시 부평구 청중로 61, 1층 일부호 (청천동)<NA>21304
67온새미로약국인천광역시 부평구 부평대로 21, 금남빌딩 102호 (부평동)032-515-532721389
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