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I have this dataframe 

     Begin    End    Duration  ID
42   40680    40846    167     18

and I want to convert a numpy array in this form :

array([40680 , 40860 ,167,18])

I am using for conversion as_matrix function and I used after it reshape(1,4) but it is not working!! It is getting me this format : [[40680 40846 167 18]] any suggestions please ? I need to convert it to that format so I can apply 'precision_recall_curve' function.

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    Try array.ravel() instead of reshape. So, if the dataframe is df : df.values.ravel() or simply : np.ravel(df). Commented Dec 24, 2016 at 9:17
  • Sorry but even this solution is not working it get me an array like this : [40680 40846 167 18] Commented Dec 24, 2016 at 9:37
  • Isn't that what you were expecting? Commented Dec 24, 2016 at 9:38
  • no . I want it to be this way : array([40680 , 40860 ,167,18]) Commented Dec 24, 2016 at 9:43
  • @jaouaemna, you seems to be confused by the result of print(array) command, which per default doesn't show comas - try @ Divakar's solution: np.ravel(df) in iPython or in Jupiter Commented Dec 24, 2016 at 13:14

1 Answer 1

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You have something like this:

pd.DataFrame({'a':[1],'b':[2],'c':[3]}, index=[42])
Out[27]: 
    a  b  c
42  1  2  3

You want to get a single row as a NumPy array:

df.loc[42].values
Out[30]: array([1, 2, 3])
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5 Comments

sorry ! but it is not working! this is what I get ! [40680 40846 167 18] and I have applied y_true = eval_seg.loc[42].values! I am sure that the input format is a dataframe this is what I get when I print type of (eval_seg) <class 'pandas.core.frame.DataFrame'>
@jaouaemna: Sorry but I have no idea what you are saying now. Maybe if you can add more detail with full executable code to your question....
well I have as input a dataframe ! and I want to convert it to numpy array as the format that I mentioned before. because I want to use that array as input in a function ''precision_recall_curve'' that calculates the precision and recall between two arrays. So when I use this array [40680 40846 167 18] the function get me as error : "ValueError: Data is not binary and pos_label is not specified"
@jaouaemna: I see. That's a different question--you need to read the docs at scikit-learn.org/stable/modules/generated/… and note that it requires "binary" input, not any numbers as you are using.
Oh I see. I didn't pay attention to that! I will see how I can calculate the precision and recall in a different way or may be I could implement the formula directly in python.

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