Write a Python function rainaverage(l)

Question

Write a Python function rainaverage(l) that takes as input a list of rainfall recordings and computes the avarage rainfall for each city. The output should be a list of pairs (c,ar)where c is the city and ar is the average rainfall for this city among the recordings in the input list. Note that arshould be of type float. The output should be sorted in dictionary order with respect to the city name.

Here are some examples to show how rainaverage(l) should work.

>>> rainaverage([(1,2),(1,3),(2,3),(1,1),(3,8)]) [(1, 2.0), (2, 3.0), (3, 8.0)] >>> rainaverage([('Bombay',848),('Madras',103),('Bombay',923),('Bangalore',201),('Madras',128)]) [('Bangalore', 201.0), ('Bombay', 885.5), ('Madras', 115.5)]

I tried this, but it didn't work. I'm struck up
import pandas as pd def l = [('Bombay',848),('Madras',103),('Bombay',923),('Bangalore',201),('Madras',128)] df = pd.DataFrame(l, columns=['city', 'rainfall']) output = [] for c in df['city'].unique(): output += [(c, df[df['city'] == c]['rainfall'].mean())] print(output)

Answer 1

I think you are really close, as all you need to implement is a .sort method on the output and wrap it into a function.
Check out the code below, it checks the validity of the mean calculation by utilizing pandas' groupby method:
https://code.sololearn.com/ckY2wAq7BeG0/?ref=app

Answer 2

In Sololearn indeed, no module is named pandas ;)
But the code should work on any environment having pandas installed.

Answer 3

Is there any other way other than pandas?

Answer 4

Of course. You can use simple lists of tuples (key, value) iterate through them and (for example) create new lists with [0] element as "key" and all others [1:] appended as discrete values -- then just display a[0], mean(a[1:])

In your case it would result in:
['Madras', 103, 128], ['Bombay', 848, 923], ['Bangalore', 201]

Answer 5

@roshini manoharan require for nptel it seems #XD

Answer 6

Hey but it says there is no module named pandas!