pandas

consider a data frame defined like so: import pandas as pd test = pd.DataFrame({ 'id' : ['a', 'b', 'c', 'd'], 'times' : [2, 3, 1, 5] }) Is it possible to create a new data frame from this in which each row is repeated times times, such that the result looks like this: >>> result … Read more

I have two dataframes, both indexed by timeseries. I need to add the elements together to form a new dataframe, but only if the index and column are the same. If the item does not exist in one of the dataframes then it should be treated as a zero.

I can use pandas dropna() functionality to remove rows with some or all columns set as NA‘s. Is there an equivalent function for dropping rows with all columns having value 0?

I have a large (about 12M rows) DataFrame df:

I know this is a very basic question but for some reason I can’t find an answer. How can I get the index of certain element of a Series in python pandas? (first occurrence would suffice)