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Classification
Medicinas y vacunas. Medicinas
IMSS product code
010.000.3305.00
Each circle represents one of the 5 purchases of COMPRA EMERGENTE made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Guanajuato | Guanajuato | 4 | 2,901.5 MXN | 0.000061 MXN | 0.000000749 % | 0.00000015 | 2 de diciembre de 2011 |
| Delegación Veracruz Norte | Veracruz | 1 | 136.8 MXN | 55.9 MXN | 69.1 % | 0.691 | 11 de agosto de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| REX FARMA, S.A. DE C.V. | 3 | - MXN | - | - | 2009 - 2010 |
| DOMINGUEZ LOPEZ MARTIN | 1 | 0.000061 MXN | 0.000003 % | 0.00000015 | 2011 - 2011 |
| SERGIO TORRES MARIN | 1 | 55.9 MXN | 69.1 % | 0.691 | 2009 - 2009 |
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=010.000.3305.00")
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=010.000.3305.00')
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=010.000.3305.00')