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Description
Compra Emergente
IMSS product code
060.167.6653.01
Each circle represents one of the 2 purchases of CATÉTERES made by the IMSS between 2010 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Jalisco | Jalisco | 1 | 1,322.4 MXN | - MXN | - | - | 7 de octubre de 2010 |
| Delegación Nuevo León | Nuevo León | 1 | 14,314.4 MXN | 717.2 MXN | 5.27 % | 1.22 | 3 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIALIZADORA GAYDI, S.A. DE C.V. | 1 | 717.2 MXN | 5.27 % | 1.22 | 2010 - 2010 |
| ROCHA MEZA MARIA GUADALUPE | 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=060.167.6653.01")
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=060.167.6653.01')
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=060.167.6653.01')