CODEWITHSUNDEEP
pythonpandas
HeinrichCode
HeinrichCode

Reputation: 69

Filling an empty list in python

I am trying to create a new list using data from a pandas Dataframe. The Dataframe in question has a column of Dates as well as a column for Units Sold as seen below:

Peep = Xsku[['new_date', 'cum_sum']]

Peep.head(15)
Out[159]: 
        new_date  cum_sum
18    2011-01-17      214
1173  2011-01-24      343
2328  2011-01-31      407 #Save Entry in List
3483  2011-02-07       71
4638  2011-02-14      159
5793  2011-02-21      294
6948  2011-02-28      425 #Save Entry in List
8103  2011-03-07      113
9258  2011-03-14      249
10413 2011-03-21      347
11568 2011-03-28      463 #Save Entry in List
12723 2011-04-04       99
13878 2011-04-11      186
15033 2011-04-18      291
16188 2011-04-25      385

I am trying to make a new list, where the list contains the maximum 'cum_sum' before the number is reset (i.e. becomes smaller). For example, in the first four entries above, the cum_sum reaches 407 and then goes back down to 71. I am thus trying to save the number 407 as well as the corresponding 'new_date' (2011-01-31 in this example) and do this for every entry.

My final List will thus have all the maximum 'cum_sum' values before it is reset. For example it will look like as follows: (First Three Expected Values)

MyList
Out[]:
new_date        cum_sum
2011-01-31      407
2011-02-28      425
2011-03-28      463
...

I have been trying to do something as a for loop, but continually run into problems:

MyList= []  ##My Empty List
for i in range(len(Peep['new_date'])):
    if Peep.iloc[i,1] > Peep.iloc[i + 1,1]:
        MyList.append(Peep.iloc[i,1])

Can anyone help me in this regard?

Upvotes: 0

Views: 65

Answers (1)

Zero
Zero

Reputation: 77027

Use .diff and filter like

In [17]: df[df['cum_sum'].diff(-1).ge(0)]
Out[17]: 
      new_date  cum_sum
2   2011-01-31      407
6   2011-02-28      425
10  2011-03-28      463

Upvotes: 2

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