[FIXED] How to prevent "pandas.read_csv" convert index column to float with arg 'dtype=np.float32'?

Issue

I have a CSV file to be read by pandas, and it has the form as following:

name,   quart2c,    p_rat,  other_col
avg,    1,          2,      3
std,    1,          2,      3

I want to pandas.read_csv() guarantee that all cells have the type of float32, except the first column('name') because that is the index column.

Hence I pass two args to it like this:

pandas.read_csv(file_path, index_col=0, dtype=np.float32)

# or like this, both failed
pandas.read_csv(file_path, index_col='name', dtype=np.float32)

But pandas still tries to convert the first column to float, and raises a exception:

ValueError: could not convert string to float: 'avg'

What I want:

1. The CSV file is made by another program coded by myself. If the structure is wrong, I can adjust it easily.
2. I want to always specify the arg dtype=np.float32, so as to check whether there are any error values. I don't want the values be interpreted to integer type also.
3. The index column "name" should be reserved as index_col, since it will be used later. This column should NOT be cut off anyway.

How should I get it?

Solution

Best is to first read in the csv with default args, giving index col, and then convert the entire df (which will not affect the index):

pd.read_csv(file_path, index_col='name').astype(float)

Answered By - Josh Friedlander