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Classification
Medicinas y vacunas. Medicinas
IMSS product code
010.000.3302.00
Each circle represents one of the 6 purchases of COMPRA EMERGENTE made by the IMSS between 2009 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Morelos | Morelos | 5 | 2,944 MXN | 172.1 MXN | 5.56 % | 0.556 | 18 de agosto de 2010 |
| Delegación Guerrero | Guerrero | 1 | 188.4 MXN | - MXN | - | - | 25 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MINERVA VILLARREAL ASCENCIO | 2 | 57.2 MXN | 4.43 % | 0.177 | 2009 - 2009 |
| Proveedor local no identificado (Compra Emergente) | 2 | 114.9 MXN | 9.47 % | 0.379 | 2010 - 2010 |
| COMERCIALIZADORA FARMACEUTICA DE CHIAPAS SA DE CV | 1 | - MXN | - | - | 2009 - 2009 |
| ORTEGA GALLEGOS GABRIELA | 1 | - MXN | - | - | 2010 - 2010 |
Entity type
Medicinas
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=010.000.3302.00")
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=010.000.3302.00')
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=010.000.3302.00')