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Description
PERMANGANATO DE POTASIO RA -(ACS) CRISTALES TA.
IMSS product code
080.830.2657.10
Each circle represents one of the 31 purchases of REACTIVOS QUÍMICOS made by the IMSS between 2009 and 2018.
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DISTRIBUIDORA LAB-HOS, S.A. DE C.V. | 9 | 5,104.7 MXN | 14.1 % | 16.1 | 2010 - 2014 |
| CONTROL TECNICO Y REPRESENTACIONES, S. A. DE C. V. | 4 | 1,597.9 MXN | 15 % | 3.68 | 2009 - 2018 |
| EIBL LABORATORIES, S.A. DE C.V. | 3 | 502.1 MXN | 19 % | 1.74 | 2009 - 2010 |
| FCD LABS, S.A. DE C.V. | 3 | 96.1 MXN | 10.5 % | 0.316 | 2012 - 2015 |
| ABASTECEDORA INTEGRAL ESPECIALIZADA, SA DE CV | 2 | 647 MXN | 62.2 % | 1.24 | 2015 - 2017 |
| CASLAB DE MEXICO, S. A. DE C. V. | 2 | 199.8 MXN | 4.5 % | 0.27 | 2018 - 2018 |
| AVISA MEDICAL, S.A. DE C.V. | 1 | 1,024.5 MXN | 54 % | 2.7 | 2014 - 2014 |
| BIO LEBEN, S.A. DE C.V. | 1 | 203.6 MXN | 79.3 % | 0.793 | 2009 - 2009 |
| CODEMED, S.A. DE C.V. | 1 | 121.8 MXN | 16.4 % | 0.164 | 2018 - 2018 |
| IMPULSORA MEDICA, S. A. DE C. V. | 1 | 64.2 MXN | 18.8 % | 0.188 | 2011 - 2011 |
| MARTHA ANDREA BARRERA MCDONALD | 1 | 2,046.5 MXN | 37.9 % | 4.55 | 2015 - 2015 |
| MEDICAMENTOS INSTITUCIONALES MEXICANOS, SA DE CV | 1 | - MXN | - | - | 2013 - 2013 |
| QUIMICA INDUSTRIAL Y DE SALUD, SA DE CV | 1 | 1,054.7 MXN | 36.8 % | 2.57 | 2012 - 2012 |
| TECSIQUIM, S.A. DE C.V. | 1 | - MXN | - | - | 2010 - 2010 |
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
Organization responsible for the import
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Add this to your code:
library(rjson)
#Read JSON data into R
data <- fromJSON(file="http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=080.830.2657.10")
Add this to your code:
import json, urllib
#Read JSON data into python
response = urllib2.urlopen('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=080.830.2657.10')
data = json.loads(response.read())
Add this to your code:
import pandas as pd
#Read JSON data into pandas
df = pd.read_json('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=080.830.2657.10')