I have a very simple dataframe like so:
In [8]: df
Out[8]:
A B C
0 2 a a
1 3 s 3
2 4 c !
3 1 f 1
My goal is to extract the first row in such a way that looks like this:
A B C
0 2 a a
As you can see the dataframe shape (1x3) is preserved and the first row still has 3 columns.
However when I type the following command df.loc[0] the output result is this:
df.loc[0]
Out[9]:
A 2
B a
C a
Name: 0, dtype: object
As you can see the row has turned into a column with 3 rows! (3x1 instead of 3x1). How is this possible? how can I simply extract the row and preserve its shape as described in my goal? Could you provide a smart and elegant way to do it?
I tried to use the transpose command .T but without success... I know I could create another dataframe where the columns are extracted by the original dataframe but this way quite tedious and not elegant I would say (pd.DataFrame({'A':[2], 'B':'a', 'C':'a'})).
Here is the dataframe if you need it:
import pandas as pd
df = pd.DataFrame({'A':[2,3,4,1], 'B':['a','s','c','f'], 'C':['a', 3, '!', 1]})