37

I have the following data frame just single column.

import pandas as pd
tdf =  pd.DataFrame({'s1' : [0,1,23.4,10,23]})

Currently it has the following shape.

In [54]: tdf.shape
Out[54]: (5, 1)

How can I convert it to a Series or a numpy vector so that the shape is simply (5,)

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1 Answer 1

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50

You can simply index the series you want. Example -

tdf['s1']

Demo -

In [24]: tdf =  pd.DataFrame({'s1' : [0,1,23.4,10,23]})

In [25]: tdf['s1']
Out[25]:
0     0.0
1     1.0
2    23.4
3    10.0
4    23.0
Name: s1, dtype: float64

In [26]: tdf['s1'].shape
Out[26]: (5,)

If you want the values in the series as numpy array, you can use .values accessor , Example -

In [27]: tdf['s1'].values
Out[27]: array([  0. ,   1. ,  23.4,  10. ,  23. ])
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4 Comments

or perhaps assign the series to a numpy array for further manipulation, ie. np.asarray(tdf['s1'])
Yea, but I think tdf['s1'].values would be cleaner.
This can have the following error stackoverflow.com/questions/39474056/…
If you wish to avoid reference to the column name, you can alternatively do tdf.iloc[:,0] to get the leftmost column, tdf.iloc[:,1] for the next one...

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