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I'd like to build a running sum over a pandas dataframe. I have something like:
10/10/2012: 50, 0
10/11/2012: -10, 90
10/12/2012: 100, -5
And I would like to get:
10/10/2012: 50, 0
10/11/2012: 40, 90
10/12/2012: 140, 85
So every cell should be the sum of itself and all previous cells, how should I do this without using a loop.
628
The cumsum() method returns a DataFrame with the cumulative sum for each row. The cumsum() method goes through the values in the DataFrame, from the top, row by row, adding the values with the value from the previous row, ending up with a DataFrame where the last row contains the sum of all values for each column.
sum() function return the sum of the values for the requested axis. If the input is index axis then it adds all the values in a column and repeats the same for all the columns and returns a series containing the sum of all the values in each column.
As @JonClements mentions, you can do this using the cumsum DataFrame method:
from pandas import DataFrame
df = DataFrame({0: {'10/10/2012': 50, '10/11/2012': -10, '10/12/2012': 100}, 1: {'10/10/2012': 0, '10/11/2012': 90, '10/12/2012': -5}})
In [3]: df
Out[3]:
0 1
10/10/2012 50 0
10/11/2012 -10 90
10/12/2012 100 -5
In [4]: df.cumsum()
Out[4]:
0 1
10/10/2012 50 0
10/11/2012 40 90
10/12/2012 140 85
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