python - The difference between double brace `[[...]]` and single brace `[..]` indexing in Pandas

Question

I'm confused about the syntax regarding the following line of code:

x_values = dataframe[['Brains']]

The dataframe object consists of 2 columns (Brains and Bodies)

Brains Bodies
42     34
32     23

When I print x_values I get something like this:

Brains
0  42
1  32

I'm aware of the pandas documentation as far as attributes and methods of the dataframe object are concerned, but the double bracket syntax is confusing me.

Answer 1

Consider this:

Source DF:

In [79]: df
Out[79]:
   Brains  Bodies
0      42      34
1      32      23

Selecting one column - results in Pandas.Series:

In [80]: df['Brains']
Out[80]:
0    42
1    32
Name: Brains, dtype: int64

In [81]: type(df['Brains'])
Out[81]: pandas.core.series.Series

Selecting subset of DataFrame - results in DataFrame:

In [82]: df[['Brains']]
Out[82]:
   Brains
0      42
1      32

In [83]: type(df[['Brains']])
Out[83]: pandas.core.frame.DataFrame

Conclusion: the second approach allows us to select multiple columns from the DataFrame. The first one just for selecting single column...

Demo:

In [84]: df = pd.DataFrame(np.random.rand(5,6), columns=list('abcdef'))

In [85]: df
Out[85]:
          a         b         c         d         e         f
0  0.065196  0.257422  0.273534  0.831993  0.487693  0.660252
1  0.641677  0.462979  0.207757  0.597599  0.117029  0.429324
2  0.345314  0.053551  0.634602  0.143417  0.946373  0.770590
3  0.860276  0.223166  0.001615  0.212880  0.907163  0.437295
4  0.670969  0.218909  0.382810  0.275696  0.012626  0.347549

In [86]: df[['e','a','c']]
Out[86]:
          e         a         c
0  0.487693  0.065196  0.273534
1  0.117029  0.641677  0.207757
2  0.946373  0.345314  0.634602
3  0.907163  0.860276  0.001615
4  0.012626  0.670969  0.382810

and if we specify only one column in the list we will get a DataFrame with one column:

In [87]: df[['e']]
Out[87]:
          e
0  0.487693
1  0.117029
2  0.946373
3  0.907163
4  0.012626