CODEWITHSUNDEEP
pythonarrayspandasnumpydataframe
Liza
Liza

Reputation: 971

How to get numpy arrays indexing equivalent in pandas data frame?

I have a numpy array as following:

    array([[1, 2],
           [3, 4],
           [5, 6],
           [7, 8]])

The array is called myArray, and I perform two indexing operations on the 2D array and get following results:

    In[1]: a1 = myArray[1:]
           a1

    Out[1]:array([[3, 4],
                 [5, 6],
                 [7, 8]])


    In[2]: a2 = myArray[:-1]
           a2

    Out[2]:array([[1, 2],
                  [3, 4],
                  [5, 6]])

Now, I have the same data in the form of a pandas df in two columns, let the data frame be df

      x    y
   0  1    2
   1  3    4
   3  5    6
   4  7    8

How to do the equivalent indexing/ slicing on two columns to get the same results as above for a1 and a2.

Upvotes: 3

Views: 24036

Answers (1)

akuiper
akuiper

Reputation: 215107

Use iloc:

df.iloc[1:]

#   x   y
#1  3   4
#3  5   6
#4  7   8

df.iloc[:-1]

#   x   y
#0  1   2
#1  3   4
#3  5   6

Use head/tail: 

df.head(-1)       # equivalent to df.iloc[:-1]

#   x   y
#0  1   2
#1  3   4
#3  5   6

df.tail(-1)       # equivalent to df.iloc[1:]

#   x   y
#1  3   4
#3  5   6
#4  7   8

Upvotes: 1

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