Can pandas
read a transposed CSV? Here's the file (note I'd also like to select a subset of columns):
A,x,x,x,x,1,2,3
B,x,x,x,x,4,5,6
C,x,x,x,x,7,8,9
Would like to get this DataFrame:
A B C
0 1 4 7
1 2 5 8
2 3 6 9
pd.read_csv('file.csv', index_col=0, header=None).T
In addition, if your file looks like this:
"some-line-you-want-to-skip"
A,x,x,x,x,1,2,3
B,x,x,x,x,4,5,6
C,x,x,x,x,7,8,9
It is possible to do the following:
df = pd.read_csv(filename, skiprows=1, header=None).T # Read csv, and transpose
df.columns = df.iloc[0] # Set new column names
df.drop(0,inplace=True) # Drop duplicated row
This will also end up with the df looking the way you want
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