dfply
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kieferk
dplyr-style piping operations for pandas dataframes
I am trying to calculate the summary statistics by grouping variable and then sorting the result in descending order. ``` #Import Data import pandas as pd mydata=pd.read_csv("http://winterolympicsmedals.com/medals.csv") #2006 Gold Medal...
Hi there, Would it be possible to add **sum()** to the summary function? I can see this feature being helpful to a lot of us especially putting together quick stats.
So I want to be to simply do a group by and count on a column with categorical values. When running the code below ``` df = pd.DataFrame({"animal": ["cat", "cat",...
Make code examples match the new function naming.
Hi, When I use the data using dfply the type of data is dfply.pipe and if I run a command like dataframe.info() it doesn’t recognise the pandas functions. How can...
missing cumcount() function in embedded column functions, especially needed for using spread() function to handle the DataFrame with duplicate identifier.
One quick note: I put `assert_known_cols()` inside `group_by()` instead of within `group_delegation.__call__()` b/c I wanted the error to be thrown even if no grouped function is called on the data....
A missing `group_by` column does not raise an exception. ```python In [15]: pd.DataFrame({'a': [1,2,2], 'b': [4,5,6]}) >> group_by('c') Out[15]: a b 0 1 4 1 2 5 2 2 6...
