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I'm trying to make some code that lets me use a function to get the price of items and sum them together quickly.
So a simplified version of my code currently looks like this:
#Header = {Item, Price, Service Tax}
Dairy = {'Milk': [2.30, 0.16, 'Yes'],
'Butter': [4.50, 0.32, 'No']}
Cart = []
Cart.append('Milk')
Cart.append('Butter')
Collective = []
Collective.append(Cart[0])
print(sum(Collective))
This results in either Unhashable error or nothing being printed at all, when I'm looking for the sum of 2.30 and 4.50.
Just try using this code:
print(sum([sublist[0] for sublist in Dairy.values()]))
Output:
6.8
If you mean that Dairy contains lots of stuff, but you only want some information, whose keys are in Cart, then you can do this:
#Header = {Item, Price, Service Tax}
Dairy = {'Milk': [2.30, 0.16, 'Yes'],
'Butter': [4.50, 0.32, 'No'],
'other': [42.50, 0.42, 'No']}
Cart = []
Cart.append('Milk')
Cart.append('Butter')
Collective = [Dairy[item][0] for item in Cart]
print(sum(Collective))
Output: 6.8
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I want to loop through this csv that has country, data, and a number I need to extract. The file looks like this:
b'/O_o/\ngoogle.visualization.Query.setResponse({"version":"0.6","reqId":"0output=csv","status":"ok","sig":"1241529276","table":{"cols":[{"id":"A","label":"Entity","type":"string"},{"id":"B","label":"Week","type":"number","pattern":"General"},{"id":"C","label":"Day","type":"date","pattern":"yyyy-mm-dd"},{"id":"D","label":"Flights
2019
(Reference)","type":"number","pattern":"General"},{"id":"E","label":"Flights","type":"number","pattern":"General"},{"id":"F","label":"%
vs 2019
(Daily)","type":"number","pattern":"General"},{"id":"G","label":"Flights
(7-day moving
average)","type":"number","pattern":"General"},{"id":"H","label":"% vs
2019 (7-day Moving
Average)","type":"number","pattern":"General"},{"id":"I","label":"Day
2019","type":"date","pattern":"yyyy-mm-dd"},{"id":"J","label":"Day
Previous
Year","type":"date","pattern":"yyyy-mm-dd"},{"id":"K","label":"Flights
Previous
Year","type":"number","pattern":"General"}],"rows":[{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,1)","f":"2020-09-01"},{"v":129.0,"f":"129"},{"v":64.0,"f":"64"},{"v":-0.503875968992248,"f":"-0,503875969"},{"v":71.5714285714286,"f":"71,57142857"},{"v":-0.291371994342291,"f":"-0,2913719943"},{"v":"Date(2019,8,3)","f":"2019-09-03"},{"v":"Date(2019,8,3)","f":"2019-09-03"},{"v":129.0,"f":"129"}]},{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,2)","f":"2020-09-02"},{"v":92.0,"f":"92"},{"v":59.0,"f":"59"},{"v":-0.358695652173913,"f":"-0,3586956522"},{"v":70.0,"f":"70"},{"v":-0.300998573466476,"f":"-0,3009985735"},{"v":"Date(2019,8,4)","f":"2019-09-04"},{"v":"Date(2019,8,4)","f":"2019-09-04"},{"v":92.0,"f":"92"}]},{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,3)","f":"2020-09-03"},{"v":96.0,"f":"96"},{"v":67.0,"f":"67"},{"v":-0.302083333333333,"f":"-0,3020833333"},{"v":70.1428571428571,"f":"70,14285714"},{"v":-0.30354609929078,"f":"-0,3035460993"},{"v":"Date(2019,8,5)","f":"2019-09-05"},{"v":"Date(2019,8,5)","f":"2019-09-05"},{"v":96.0,"f":"96"}]},{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,4)","f":"2020-09-04"},{"v":103.0,"f":"103"},{"v":89.0,"f":"89"},{"v":-0.135922330097087,"f":"-0,1359223301"},{"v":69.2857142857143,"f":"69,28571429"},{"v":-0.312056737588652,"f":"-0,3120567376"},{"v":"Date(2019,8,6)","f":"2019-09-06"},{"v":"Date(2019,8,6)","f":"2019-09-06"},{"v":103.0,"f":"103"}]},{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,5)","f":"2020-09-05"},{"v":94.0,"f":"94"},{"v":53.0,"f":"53"},{"v":-0.436170212765957,"f":"-0,4361702128"},{"v":68.8571428571429,"f":"68,85714286"},{"v":-0.314366998577525,"f":"-0,3143669986"},{"v":"Date(2019,8,7)","f":"2019-09-07"},{"v":"Date(2019,8,7)","f":"2019-09-07"},{"v":94.0,"f":"94"}]}, ...
In there it says Albania, which is a country with data I need to extract. For example:
{"c":[{"v":"Albania"},{"v":36.0,"f":"36"},{"v":"Date(2020,8,4)","f":"2020-09-04"},{"v":103.0,"f":"103"},{"v":89.0,"f":"89"},{"v":-0.135922330097087,"f":"-0,1359223301"},{"v":69.2857142857143,"f":"69,28571429"},{"v":-0.312056737588652,"f":"-0,3120567376"},{"v":"Date(2019,8,6)","f":"2019-09-06"},{"v":"Date(2019,8,6)","f":"2019-09-06"},{"v":103.0,"f":"103"}]}
How would I write a python script to loop over the entire csv file and find every occurrence of the word "Albania", save it, then go a little further and get the date "2020-09-04", and then get the number -0.1359?
You can read this using json.
import json
with open('txtfile1.txt') as input:
data = input.read()
#Select the part where the dictionary start (after "rows":)
nesteddict = json.loads(data[(data.find('rows')+6):])
finallist = []
for x in nesteddict:
sublist = []
sublist.append(x['c'][0]['v'])
sublist.append(x['c'][2]['f'])
sublist.append(x['c'][5]['v'])
finallist.append(sublist)
This will output
[['Albania', '2020-09-01', -0.503875968992248], ['Albania', '2020-09-02', -0.358695652173913], ['Albania', '2020-09-03', -0.302083333333333], ['Albania', '2020-09-04', -0.135922330097087], ['Albania', '2020-09-05', -0.436170212765957]]
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I have below list:
list_a = ['USD', 'Notional Amount:', 'USD', '50,000,000.00', 'KRW', 'Notional Amount:', 'KRW', '53,585,000,000']
list_a include Currency code like 'usd' and amount like 50,000,000.00
By using python, I want to classify following:
am_list = [50000000,53585000000]
cu_list = ['USD','USD','KRW' 'KRW']
Anyone who will solve it easily give me solution please.
Just loop over it and check the type of element:
import re
list_a = ['USD', 'Notional Amount:', 'USD', '50,000,000.00', 'KRW', 'Notional Amount:', 'KRW', '53,585,000,000']
am_list = []
cu_list = []
for element in list_a:
# if element is number like combination of "number" and "," and "."
if re.match('^[\d\.,]+$', element):
am_list.append(element)
# curency symble 2 or 3 letters
if re.match('^[A-Z]{2,3}$', element):
cu_list.append(element)
print(am_list) # ['50,000,000.00', '53,585,000,000']
print(cu_list) # ['USD', 'USD', 'KRW', 'KRW']
If you want to make sure it's a valid amount that looks like this : '50,000,000.00', '50.00', '50,000.00', '50' ... etc:
re.match('^(\d+,)*\d+(\.\d+)?$', element)