Converting Pandas Dataframe to numpy array

Question

The following is a Pandas dataframe df

index_column      value_column
 0                   20
 2                   28
 1                   30

It needs to be converted into a numpy array where index_column becomes the index of numpy array and value_column becomes the corresponding value.

That is np_arr[0]=20, np_arr[1]=30, np_arr[2]=28 and so on.

How can this be achieved?

And what happens when `index_column` isn't a RangeIndex starting from 0? `numpy` array indexing is 0 based, so do you need this to work in general for any arbitrary index arrangement? — ALollz, Mar 13 '19 at 18:21
index_column will have 0 to n rows,where n is number of rows in dataframe.But they may not be in ascending order. — TLanni, Mar 13 '19 at 18:25
1) this has been asked before, and 2) please don't follow any of the answers below if you're using 0.24. — cs95, Mar 13 '19 at 18:31

Ashish kulkarni · Answer 1 · 2019-03-13T18:30:00.983

2

np_arr = df.value_column.values

edited Mar 13 '19 at 18:30

answered Mar 13 '19 at 18:18

Ashish kulkarni

@amandasmith: What you have mentioned is a good way to do it. – Ashish kulkarni Mar 13 '19 at 18:29

score 2 · Answer 2 · answered Mar 13 '19 at 18:25

2

Pandas internally uses np.arrays. The values attribute is all you need:

df.value_column.values

is the np.array that you want.

answered Mar 13 '19 at 18:25

Serge Ballesta

sourebh_s · Answer 3 · 2019-03-13T18:31:01.230

1

np_arr = df.value_column.values

if your column name has special characters like space, use the following:

np_arr = df['temperature [Celsius]'].values

edited Mar 13 '19 at 18:31

answered Mar 13 '19 at 18:25

sourebh_s

3 Answers3