Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory847.2 KiB
Average record size in memory867.6 B

Variable types

Numeric2
Text5
Categorical5

Alerts

expediente_invima is highly overall correlated with unidad_base and 1 other fieldsHigh correlation
factoresprecio is highly overall correlated with numerofactorHigh correlation
numerofactor is highly overall correlated with factoresprecioHigh correlation
unidad_base is highly overall correlated with expediente_invima and 1 other fieldsHigh correlation
unidad_de_dispensacion is highly overall correlated with expediente_invima and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-11-12 06:00:58.377129
Analysis finished2024-11-12 06:01:24.419454
Duration26.04 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

expediente_invima
Real number (ℝ)

High correlation 

Distinct553
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16989992
Minimum10815
Maximum19932353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-12T06:01:24.645114image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum10815
5-th percentile19512
Q119903368
median19912760
Q319927074
95-th percentile19931121
Maximum19932353
Range19921538
Interquartile range (IQR)23706

Descriptive statistics

Standard deviation6822522.8
Coefficient of variation (CV)0.40156126
Kurtosis1.6836519
Mean16989992
Median Absolute Deviation (MAD)11746.5
Skewness-1.9120285
Sum1.6989992 × 1010
Variance4.6546817 × 1013
MonotonicityNot monotonic
2024-11-12T06:01:25.114017image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19907869 8
 
0.8%
19906457 5
 
0.5%
19929516 4
 
0.4%
19930887 4
 
0.4%
19930439 4
 
0.4%
19906441 4
 
0.4%
19918906 4
 
0.4%
19901079 4
 
0.4%
19908091 4
 
0.4%
19929593 4
 
0.4%
Other values (543) 955
95.5%
ValueCountFrequency (%)
10815 1
0.1%
11415 1
0.1%
11416 2
0.2%
11697 2
0.2%
11699 2
0.2%
11700 2
0.2%
11701 2
0.2%
11849 1
0.1%
11878 2
0.2%
11879 2
0.2%
ValueCountFrequency (%)
19932353 2
0.2%
19932247 2
0.2%
19932174 2
0.2%
19932170 1
 
0.1%
19932152 2
0.2%
19932135 4
0.4%
19932108 1
 
0.1%
19932060 2
0.2%
19932059 1
 
0.1%
19931883 1
 
0.1%
Distinct326
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size70.7 KiB
2024-11-12T06:01:25.584678image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length80
Median length51
Mean length15.312
Min length7

Characters and Unicode

Total characters15312
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)6.2%

Sample

1st rowMidazolam
2nd rowAcido Valproico
3rd rowAcido Valproico
4th rowFluoxetina
5th rowProximetacaina
ValueCountFrequency (%)
y 93
 
5.6%
84
 
5.0%
de 60
 
3.6%
acetaminofen 36
 
2.2%
acido 25
 
1.5%
hidroclorotiazida 21
 
1.3%
clotrimazol 20
 
1.2%
ibuprofeno 17
 
1.0%
levotiroxina 16
 
1.0%
sodica 16
 
1.0%
Other values (370) 1279
76.7%
2024-11-12T06:01:26.557820image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1727
 
11.3%
i 1715
 
11.2%
o 1650
 
10.8%
n 1122
 
7.3%
e 954
 
6.2%
l 866
 
5.7%
r 859
 
5.6%
t 805
 
5.3%
667
 
4.4%
c 530
 
3.5%
Other values (46) 4417
28.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1727
 
11.3%
i 1715
 
11.2%
o 1650
 
10.8%
n 1122
 
7.3%
e 954
 
6.2%
l 866
 
5.7%
r 859
 
5.6%
t 805
 
5.3%
667
 
4.4%
c 530
 
3.5%
Other values (46) 4417
28.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1727
 
11.3%
i 1715
 
11.2%
o 1650
 
10.8%
n 1122
 
7.3%
e 954
 
6.2%
l 866
 
5.7%
r 859
 
5.6%
t 805
 
5.3%
667
 
4.4%
c 530
 
3.5%
Other values (46) 4417
28.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1727
 
11.3%
i 1715
 
11.2%
o 1650
 
10.8%
n 1122
 
7.3%
e 954
 
6.2%
l 866
 
5.7%
r 859
 
5.6%
t 805
 
5.3%
667
 
4.4%
c 530
 
3.5%
Other values (46) 4417
28.8%
Distinct466
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size79.3 KiB
2024-11-12T06:01:26.992689image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length89
Median length72
Mean length23.658
Min length11

Characters and Unicode

Total characters23658
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)11.9%

Sample

1st rowMidazolam 15 mg
2nd rowDivalproato Sodico 500 mg
3rd rowDivalproato Sodico 500 mg
4th rowFluoxetina 20 mg
5th rowProximetacaina 5 mg
ValueCountFrequency (%)
mg 830
 
20.0%
g 226
 
5.4%
205
 
4.9%
500 83
 
2.0%
1 83
 
2.0%
de 80
 
1.9%
10 75
 
1.8%
mcg 75
 
1.8%
50 73
 
1.8%
100 66
 
1.6%
Other values (490) 2353
56.7%
2024-11-12T06:01:27.570738image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3151
 
13.3%
a 1809
 
7.6%
i 1797
 
7.6%
o 1754
 
7.4%
m 1380
 
5.8%
g 1176
 
5.0%
n 1163
 
4.9%
0 1113
 
4.7%
e 1029
 
4.3%
l 907
 
3.8%
Other values (57) 8379
35.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23658
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3151
 
13.3%
a 1809
 
7.6%
i 1797
 
7.6%
o 1754
 
7.4%
m 1380
 
5.8%
g 1176
 
5.0%
n 1163
 
4.9%
0 1113
 
4.7%
e 1029
 
4.3%
l 907
 
3.8%
Other values (57) 8379
35.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23658
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3151
 
13.3%
a 1809
 
7.6%
i 1797
 
7.6%
o 1754
 
7.4%
m 1380
 
5.8%
g 1176
 
5.0%
n 1163
 
4.9%
0 1113
 
4.7%
e 1029
 
4.3%
l 907
 
3.8%
Other values (57) 8379
35.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23658
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3151
 
13.3%
a 1809
 
7.6%
i 1797
 
7.6%
o 1754
 
7.4%
m 1380
 
5.8%
g 1176
 
5.0%
n 1163
 
4.9%
0 1113
 
4.7%
e 1029
 
4.3%
l 907
 
3.8%
Other values (57) 8379
35.4%

unidad_base
Categorical

High correlation 

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
mg
530 
ml
293 
g
118 
mcg
 
23
dosis
 
20
Other values (2)
 
16

Length

Max length5
Median length2
Mean length1.966
Min length1

Characters and Unicode

Total characters1966
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowml
2nd rowmg
3rd rowmg
4th rowmg
5th rowml

Common Values

ValueCountFrequency (%)
mg 530
53.0%
ml 293
29.3%
g 118
 
11.8%
mcg 23
 
2.3%
dosis 20
 
2.0%
IU 15
 
1.5%
MIU 1
 
0.1%

Length

2024-11-12T06:01:27.792222image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-12T06:01:27.966647image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
mg 530
53.0%
ml 293
29.3%
g 118
 
11.8%
mcg 23
 
2.3%
dosis 20
 
2.0%
iu 15
 
1.5%
miu 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
m 846
43.0%
g 671
34.1%
l 293
 
14.9%
s 40
 
2.0%
c 23
 
1.2%
d 20
 
1.0%
o 20
 
1.0%
i 20
 
1.0%
I 16
 
0.8%
U 16
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1966
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
m 846
43.0%
g 671
34.1%
l 293
 
14.9%
s 40
 
2.0%
c 23
 
1.2%
d 20
 
1.0%
o 20
 
1.0%
i 20
 
1.0%
I 16
 
0.8%
U 16
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1966
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
m 846
43.0%
g 671
34.1%
l 293
 
14.9%
s 40
 
2.0%
c 23
 
1.2%
d 20
 
1.0%
o 20
 
1.0%
i 20
 
1.0%
I 16
 
0.8%
U 16
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1966
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
m 846
43.0%
g 671
34.1%
l 293
 
14.9%
s 40
 
2.0%
c 23
 
1.2%
d 20
 
1.0%
o 20
 
1.0%
i 20
 
1.0%
I 16
 
0.8%
U 16
 
0.8%

unidad_de_dispensacion
Categorical

High correlation 

Distinct18
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size62.2 KiB
Tableta
406 
Frasco
162 
Capsula
109 
Ampolla
82 
Vial
75 
Other values (13)
166 

Length

Max length21
Median length7
Mean length6.613
Min length4

Characters and Unicode

Total characters6613
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowAmpolla
2nd rowTableta
3rd rowTableta
4th rowCapsula
5th rowFrasco

Common Values

ValueCountFrequency (%)
Tableta 406
40.6%
Frasco 162
 
16.2%
Capsula 109
 
10.9%
Ampolla 82
 
8.2%
Vial 75
 
7.5%
Tubo 69
 
6.9%
Inhalador 24
 
2.4%
Bolsa 17
 
1.7%
Jeringa Prellenada 14
 
1.4%
Sobre 9
 
0.9%
Other values (8) 33
 
3.3%

Length

2024-11-12T06:01:28.172696image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tableta 411
40.3%
frasco 162
 
15.9%
capsula 109
 
10.7%
ampolla 82
 
8.0%
vial 75
 
7.3%
tubo 69
 
6.8%
inhalador 24
 
2.4%
bolsa 17
 
1.7%
jeringa 14
 
1.4%
prellenada 14
 
1.4%
Other values (10) 44
 
4.3%

Most occurring characters

ValueCountFrequency (%)
a 1494
22.6%
l 865
13.1%
b 494
 
7.5%
e 484
 
7.3%
T 480
 
7.3%
t 430
 
6.5%
o 389
 
5.9%
s 297
 
4.5%
r 236
 
3.6%
p 198
 
3.0%
Other values (22) 1246
18.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6613
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1494
22.6%
l 865
13.1%
b 494
 
7.5%
e 484
 
7.3%
T 480
 
7.3%
t 430
 
6.5%
o 389
 
5.9%
s 297
 
4.5%
r 236
 
3.6%
p 198
 
3.0%
Other values (22) 1246
18.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6613
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1494
22.6%
l 865
13.1%
b 494
 
7.5%
e 484
 
7.3%
T 480
 
7.3%
t 430
 
6.5%
o 389
 
5.9%
s 297
 
4.5%
r 236
 
3.6%
p 198
 
3.0%
Other values (22) 1246
18.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6613
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1494
22.6%
l 865
13.1%
b 494
 
7.5%
e 484
 
7.3%
T 480
 
7.3%
t 430
 
6.5%
o 389
 
5.9%
s 297
 
4.5%
r 236
 
3.6%
p 198
 
3.0%
Other values (22) 1246
18.8%
Distinct427
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2024-11-12T06:01:28.460556image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length40
Median length29
Mean length10.473
Min length5

Characters and Unicode

Total characters10473
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)10.7%

Sample

1st rowDormicum
2nd rowValcote
3rd rowValcote
4th rowFluoxetina
5th rowAlcaine
ValueCountFrequency (%)
de 35
 
2.6%
synthroid 16
 
1.2%
atorvastatina 12
 
0.9%
2 12
 
0.9%
cloruro 10
 
0.7%
seretide 10
 
0.7%
10
 
0.7%
crema 10
 
0.7%
plus 10
 
0.7%
clotrimazol 10
 
0.7%
Other values (481) 1206
89.9%
2024-11-12T06:01:28.997217image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1066
 
10.2%
o 967
 
9.2%
i 955
 
9.1%
e 752
 
7.2%
r 661
 
6.3%
n 651
 
6.2%
l 626
 
6.0%
t 548
 
5.2%
341
 
3.3%
c 317
 
3.0%
Other values (55) 3589
34.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10473
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1066
 
10.2%
o 967
 
9.2%
i 955
 
9.1%
e 752
 
7.2%
r 661
 
6.3%
n 651
 
6.2%
l 626
 
6.0%
t 548
 
5.2%
341
 
3.3%
c 317
 
3.0%
Other values (55) 3589
34.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10473
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1066
 
10.2%
o 967
 
9.2%
i 955
 
9.1%
e 752
 
7.2%
r 661
 
6.3%
n 651
 
6.2%
l 626
 
6.0%
t 548
 
5.2%
341
 
3.3%
c 317
 
3.0%
Other values (55) 3589
34.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10473
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1066
 
10.2%
o 967
 
9.2%
i 955
 
9.1%
e 752
 
7.2%
r 661
 
6.3%
n 651
 
6.2%
l 626
 
6.0%
t 548
 
5.2%
341
 
3.3%
c 317
 
3.0%
Other values (55) 3589
34.3%
Distinct124
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size65.2 KiB
2024-11-12T06:01:29.335194image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length33
Median length22
Mean length9.01
Min length2

Characters and Unicode

Total characters9010
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.5%

Sample

1st rowSiegfried
2nd rowLafrancol
3rd rowLafrancol
4th rowGenfar
5th rowAlcon
ValueCountFrequency (%)
genfar 68
 
5.6%
tecnoquimicas 54
 
4.4%
pfizer 42
 
3.4%
lafrancol 42
 
3.4%
sanofi 33
 
2.7%
aventis 33
 
2.7%
procaps 33
 
2.7%
glaxosmithkline 31
 
2.5%
merck 29
 
2.4%
la 24
 
2.0%
Other values (145) 829
68.1%
2024-11-12T06:01:29.870260image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 979
 
10.9%
e 901
 
10.0%
r 707
 
7.8%
i 660
 
7.3%
n 659
 
7.3%
o 495
 
5.5%
s 465
 
5.2%
c 407
 
4.5%
f 319
 
3.5%
l 266
 
3.0%
Other values (43) 3152
35.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9010
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 979
 
10.9%
e 901
 
10.0%
r 707
 
7.8%
i 660
 
7.3%
n 659
 
7.3%
o 495
 
5.5%
s 465
 
5.2%
c 407
 
4.5%
f 319
 
3.5%
l 266
 
3.0%
Other values (43) 3152
35.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9010
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 979
 
10.9%
e 901
 
10.0%
r 707
 
7.8%
i 660
 
7.3%
n 659
 
7.3%
o 495
 
5.5%
s 465
 
5.2%
c 407
 
4.5%
f 319
 
3.5%
l 266
 
3.0%
Other values (43) 3152
35.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9010
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 979
 
10.9%
e 901
 
10.0%
r 707
 
7.8%
i 660
 
7.3%
n 659
 
7.3%
o 495
 
5.5%
s 465
 
5.2%
c 407
 
4.5%
f 319
 
3.5%
l 266
 
3.0%
Other values (43) 3152
35.0%
Distinct607
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size135.1 KiB
2024-11-12T06:01:30.205556image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length160
Median length119
Mean length77.425
Min length53

Characters and Unicode

Total characters77425
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)21.4%

Sample

1st rowDormicum (Siegfried) - Ampolla 3 ml - Cada 3 ml contiene: Midazolam 15 mg
2nd rowValcote (Lafrancol) - Cada Tableta contiene: Divalproato Sodico 500 mg
3rd rowValcote (Lafrancol) - Cada Tableta contiene: Divalproato Sodico 500 mg
4th rowFluoxetina (Genfar) - Cada Capsula contiene: Fluoxetina 20 mg
5th rowAlcaine (Alcon) - Frasco 15 ml - Cada 1 ml contiene: Proximetacaina 5 mg
ValueCountFrequency (%)
1626
 
12.7%
cada 1000
 
7.8%
contiene 1000
 
7.8%
mg 842
 
6.6%
ml 599
 
4.7%
tableta 411
 
3.2%
g 396
 
3.1%
1 268
 
2.1%
100 243
 
1.9%
frasco 162
 
1.3%
Other values (1029) 6222
48.7%
2024-11-12T06:01:30.772768image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11771
15.2%
a 7348
 
9.5%
e 5166
 
6.7%
o 4645
 
6.0%
i 4548
 
5.9%
n 4531
 
5.9%
l 3256
 
4.2%
t 3120
 
4.0%
m 2639
 
3.4%
c 2518
 
3.3%
Other values (70) 27883
36.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 77425
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
11771
15.2%
a 7348
 
9.5%
e 5166
 
6.7%
o 4645
 
6.0%
i 4548
 
5.9%
n 4531
 
5.9%
l 3256
 
4.2%
t 3120
 
4.0%
m 2639
 
3.4%
c 2518
 
3.3%
Other values (70) 27883
36.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 77425
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
11771
15.2%
a 7348
 
9.5%
e 5166
 
6.7%
o 4645
 
6.0%
i 4548
 
5.9%
n 4531
 
5.9%
l 3256
 
4.2%
t 3120
 
4.0%
m 2639
 
3.4%
c 2518
 
3.3%
Other values (70) 27883
36.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 77425
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
11771
15.2%
a 7348
 
9.5%
e 5166
 
6.7%
o 4645
 
6.0%
i 4548
 
5.9%
n 4531
 
5.9%
l 3256
 
4.2%
t 3120
 
4.0%
m 2639
 
3.4%
c 2518
 
3.3%
Other values (70) 27883
36.0%

canal
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
Comercial
528 
Institucional
472 

Length

Max length13
Median length9
Mean length10.888
Min length9

Characters and Unicode

Total characters10888
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInstitucional
2nd rowComercial
3rd rowInstitucional
4th rowComercial
5th rowComercial

Common Values

ValueCountFrequency (%)
Comercial 528
52.8%
Institucional 472
47.2%

Length

2024-11-12T06:01:30.991366image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-12T06:01:31.143104image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
comercial 528
52.8%
institucional 472
47.2%

Most occurring characters

ValueCountFrequency (%)
i 1472
13.5%
o 1000
9.2%
c 1000
9.2%
a 1000
9.2%
l 1000
9.2%
n 944
8.7%
t 944
8.7%
C 528
 
4.8%
m 528
 
4.8%
e 528
 
4.8%
Other values (4) 1944
17.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10888
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1472
13.5%
o 1000
9.2%
c 1000
9.2%
a 1000
9.2%
l 1000
9.2%
n 944
8.7%
t 944
8.7%
C 528
 
4.8%
m 528
 
4.8%
e 528
 
4.8%
Other values (4) 1944
17.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10888
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1472
13.5%
o 1000
9.2%
c 1000
9.2%
a 1000
9.2%
l 1000
9.2%
n 944
8.7%
t 944
8.7%
C 528
 
4.8%
m 528
 
4.8%
e 528
 
4.8%
Other values (4) 1944
17.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10888
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1472
13.5%
o 1000
9.2%
c 1000
9.2%
a 1000
9.2%
l 1000
9.2%
n 944
8.7%
t 944
8.7%
C 528
 
4.8%
m 528
 
4.8%
e 528
 
4.8%
Other values (4) 1944
17.9%

precio_por_tableta
Real number (ℝ)

Distinct979
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42502.925
Minimum0.41557789
Maximum8096666.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-11-12T06:01:31.319954image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.41557789
5-th percentile93.195876
Q1732.4054
median2810.0284
Q313487.242
95-th percentile99797.148
Maximum8096666.7
Range8096666.3
Interquartile range (IQR)12754.837

Descriptive statistics

Standard deviation312805.82
Coefficient of variation (CV)7.3596304
Kurtosis464.06461
Mean42502.925
Median Absolute Deviation (MAD)2569.9023
Skewness19.693376
Sum42502925
Variance9.7847482 × 1010
MonotonicityNot monotonic
2024-11-12T06:01:31.560497image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1750 3
 
0.3%
1475227 2
 
0.2%
4648.666667 2
 
0.2%
397348 2
 
0.2%
5656 2
 
0.2%
26504 2
 
0.2%
250000 2
 
0.2%
6220 2
 
0.2%
306.4545455 2
 
0.2%
6380 2
 
0.2%
Other values (969) 979
97.9%
ValueCountFrequency (%)
0.4155778894 1
0.1%
0.6419291045 1
0.1%
2.8 1
0.1%
2.864129176 1
0.1%
2.933333333 1
0.1%
4.035476839 1
0.1%
4.236489726 1
0.1%
4.579038462 1
0.1%
6.343015873 1
0.1%
6.973516949 1
0.1%
ValueCountFrequency (%)
8096666.667 1
0.1%
3560621 1
0.1%
2856140.561 1
0.1%
1614836.99 1
0.1%
1475227 2
0.2%
1014406.686 1
0.1%
820899.284 1
0.1%
763672.5779 1
0.1%
703654 1
0.1%
626717.0858 1
0.1%

factoresprecio
Categorical

High correlation 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size60.2 KiB
Medio
550 
Alto
265 
Bajo
185 

Length

Max length5
Median length5
Mean length4.55
Min length4

Characters and Unicode

Total characters4550
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlto
2nd rowMedio
3rd rowMedio
4th rowMedio
5th rowMedio

Common Values

ValueCountFrequency (%)
Medio 550
55.0%
Alto 265
26.5%
Bajo 185
 
18.5%

Length

2024-11-12T06:01:31.762136image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-12T06:01:31.903632image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
medio 550
55.0%
alto 265
26.5%
bajo 185
 
18.5%

Most occurring characters

ValueCountFrequency (%)
o 1000
22.0%
M 550
12.1%
e 550
12.1%
d 550
12.1%
i 550
12.1%
A 265
 
5.8%
l 265
 
5.8%
t 265
 
5.8%
B 185
 
4.1%
a 185
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4550
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1000
22.0%
M 550
12.1%
e 550
12.1%
d 550
12.1%
i 550
12.1%
A 265
 
5.8%
l 265
 
5.8%
t 265
 
5.8%
B 185
 
4.1%
a 185
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4550
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1000
22.0%
M 550
12.1%
e 550
12.1%
d 550
12.1%
i 550
12.1%
A 265
 
5.8%
l 265
 
5.8%
t 265
 
5.8%
B 185
 
4.1%
a 185
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4550
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1000
22.0%
M 550
12.1%
e 550
12.1%
d 550
12.1%
i 550
12.1%
A 265
 
5.8%
l 265
 
5.8%
t 265
 
5.8%
B 185
 
4.1%
a 185
 
4.1%

numerofactor
Categorical

High correlation 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size56.8 KiB
2
550 
3
265 
1
185 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1000
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Length

2024-11-12T06:01:32.058212image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-12T06:01:32.622185image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Most occurring characters

ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 550
55.0%
3 265
26.5%
1 185
 
18.5%

Interactions

2024-11-12T06:01:10.332146image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-12T06:00:59.103004image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-12T06:01:16.829299image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-11-12T06:01:03.952970image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-11-12T06:01:32.737163image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
canalexpediente_invimafactoresprecionumerofactorprecio_por_tabletaunidad_baseunidad_de_dispensacion
canal1.0000.0000.0110.0110.0000.0000.070
expediente_invima0.0001.0000.3760.376-0.0010.6710.638
factoresprecio0.0110.3761.0001.0000.0640.0690.114
numerofactor0.0110.3761.0001.0000.0640.0690.114
precio_por_tableta0.000-0.0010.0640.0641.0000.1430.144
unidad_base0.0000.6710.0690.0690.1431.0000.626
unidad_de_dispensacion0.0700.6380.1140.1140.1440.6261.000

Missing values

2024-11-12T06:01:23.930938image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-12T06:01:24.219083image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

expediente_invimaprincipio_activoconcentracionunidad_baseunidad_de_dispensacionnombre_comercialfabricantemedicamentocanalprecio_por_tabletafactoresprecionumerofactor
0103795MidazolamMidazolam 15 mgmlAmpollaDormicumSiegfriedDormicum (Siegfried) - Ampolla 3 ml - Cada 3 ml contiene: Midazolam 15 mgInstitucional11199.8Alto3
1104739Acido ValproicoDivalproato Sodico 500 mgmgTabletaValcoteLafrancolValcote (Lafrancol) - Cada Tableta contiene: Divalproato Sodico 500 mgComercial3752.866667Medio2
2104739Acido ValproicoDivalproato Sodico 500 mgmgTabletaValcoteLafrancolValcote (Lafrancol) - Cada Tableta contiene: Divalproato Sodico 500 mgInstitucional1777.266522Medio2
310815FluoxetinaFluoxetina 20 mgmgCapsulaFluoxetinaGenfarFluoxetina (Genfar) - Cada Capsula contiene: Fluoxetina 20 mgComercial329.295281Medio2
4111057ProximetacainaProximetacaina 5 mgmlFrascoAlcaineAlconAlcaine (Alcon) - Frasco 15 ml - Cada 1 ml contiene: Proximetacaina 5 mgComercial64184.74576Medio2
5111057ProximetacainaProximetacaina 5 mgmlFrascoAlcaineAlconAlcaine (Alcon) - Frasco 15 ml - Cada 1 ml contiene: Proximetacaina 5 mgInstitucional45600Medio2
6113757Immunoglobulina AntitimocitoImmunoglobulina Antitimocito 25 mgmgVialTimoglobulinaGenzymeTimoglobulina (Genzyme) - Cada Vial contiene: Immunoglobulina Antitimocito 25 mgInstitucional626717.0858Medio2
711415AlopurinolAlopurinol 300 mgmgTabletaAlopurinolMemphisAlopurinol (Memphis) - Cada Tableta contiene: Alopurinol 300 mgComercial365.3996782Bajo1
811416HaloperidolHaloperidol 10 mgmgTabletaHaloperidolMemphisHaloperidol (Memphis) - Cada Tableta contiene: Haloperidol 10 mgComercial544.4616667Alto3
911416HaloperidolHaloperidol 10 mgmgTabletaHaloperidolMemphisHaloperidol (Memphis) - Cada Tableta contiene: Haloperidol 10 mgInstitucional2.933333333Bajo1
expediente_invimaprincipio_activoconcentracionunidad_baseunidad_de_dispensacionnombre_comercialfabricantemedicamentocanalprecio_por_tabletafactoresprecionumerofactor
99019932135Betametasona + Neomicina + ClotrimazolNeomicina 0,5 g + Betametasona 0,04 mg + Clotrimazol 1 ggTuboBetametasonaGenfarBetametasona (Genfar) - Tubo 40 g - Cada 100 g contiene: Neomicina 0,5 g + Betametasona 0,04 mg + Clotrimazol 1 gInstitucional2935.287613Medio2
99119932152CiclosporinaCiclosporina 1 mgmlFrascoModusikSophiaModusik (Sophia) - Frasco 5 ml - Cada 1 ml contiene: Ciclosporina 1 mgComercial166678.2419Medio2
99219932152CiclosporinaCiclosporina 1 mgmlFrascoModusikSophiaModusik (Sophia) - Frasco 5 ml - Cada 1 ml contiene: Ciclosporina 1 mgInstitucional128830.965Medio2
99319932170TenecteplasaTenecteplasa 50 mgmgVialMetalyseBoehringerMetalyse (Boehringer) - Cada Vial contiene: Tenecteplasa 50 mgInstitucional2856140.561Medio2
99419932174MetoclopramidaMetoclopramida 10 mgmgTabletaPlasilBussiéPlasil (Bussié) - Cada Tableta contiene: Metoclopramida 10 mgComercial1729.481777Alto3
99519932174MetoclopramidaMetoclopramida 10 mgmgTabletaPlasilBussiéPlasil (Bussié) - Cada Tableta contiene: Metoclopramida 10 mgInstitucional251.8541667Alto3
99619932247GalantaminaGalantamina 400 mgmlFrascoReminylJanssenReminyl (Janssen) - Frasco 100 ml - Cada 100 ml contiene: Galantamina 400 mgComercial472437.0579Medio2
99719932247GalantaminaGalantamina 400 mgmlFrascoReminylJanssenReminyl (Janssen) - Frasco 100 ml - Cada 100 ml contiene: Galantamina 400 mgInstitucional455593.287Medio2
99819932353CefuroximaCefuroxima 500 mgmgTabletaCefuroximaGenfarCefuroxima (Genfar) - Cada Tableta contiene: Cefuroxima 500 mgComercial3663.509646Medio2
99919932353CefuroximaCefuroxima 500 mgmgTabletaCefuroximaGenfarCefuroxima (Genfar) - Cada Tableta contiene: Cefuroxima 500 mgInstitucional2354Bajo1