The title is kind of misleading because I don't really know how to describe this
Let say that I have a nested list that looks like this:
a = [[1234,'1/8/2014'],[4123,'1/3/2014'],[5754,'1/12/2014'],[8548,'11/8/2014'],[9469,'11/9/2013'],[3564,'1/8/2013']]
In this nested list, there are 4 lists with year 2014, and 2 lists with year 2013.
I want to get an average of each year's value. So for year 2014, I want to do,
(1234 + 4123 + 5754 + 8548) / 4
and for year 2013,
(9469 + 3564) / 2
I need to get the occurrences of each year because I need to average out the sums for each year. At the end, I want something like,
new = [[4914.75, '2014'],[6516.5, '2013']]
Please note that dates are not in '01/03/2014', but just '1/3/2014'
How can this be done?
You can use Pandas to do this.
import pandas as pd
a = [[1234,'1/8/2014'],[4123,'1/3/2014'],[5754,'1/12/2014'],[8548,'11/8/2014'],[9469,'11/9/2013'],[3564,'1/8/2013']]
df = pd.DataFrame(a)
df[1] = pd.to_datetime(df[1])
df = df.set_index(1)
df.groupby(df.index.year.astype(str)).mean()\
.reset_index().values.tolist()
Output:
[['2013', 6516.5], ['2014', 4914.75]]
The above answer works and if you are not comfortable using pandas, you can refer this one.
a = [[1234,'1/8/2014'],[4123,'1/3/2014'],[5754,'1/12/2014'],[8548,'11/8/2014'],[9469,'11/9/2013'],[3564,'1/8/2013']]
data = {}
result = []
for item in a:
year = item[1].split('/')[-1]
data[year] = data.get(year, []) + [item[0]]
for key in data.keys():
items = data.get(key)
avg = sum(items)/len(items)
result.extend([key, avg])
print(result)
Try this (it assumes the inner lists are always of length 2 and that the 2nd one is a date):
from collections import defaultdict
cumulatives = defaultdict(int)
counts = defaultdict(int)
for (amount, dt) in a:
key = dt[-4:]
cumulatives[key] += amount
counts[key] += 1.0
output = [[cumulatives[key]/counts[key], key] for key in cumulatives.keys()]
print(output)
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