Answer #1:

In order to read a csv in that doesn’t have a header and for only certain columns you need to pass params header=None and usecols=[3,6] for the 4th and 7th columns:

df = pd.read_csv(file_path, header=None, usecols=[3,6])

See the docs

Answer #2:

Previous answers were good and correct, but in my opinion, an extra names parameter will make it perfect, and it should be the recommended way, especially when the csv has no headers.

Solution

Use usecols and names parameters

df = pd.read_csv(file_path, usecols=[3,6], names=['colA', 'colB'])

Additional reading

or use header=None to explicitly tells people that the csv has no headers (anyway both lines are identical)

df = pd.read_csv(file_path, usecols=[3,6], names=['colA', 'colB'], header=None)

So that you can retrieve your data by

# with `names` parameter
df['colA']
df['colB'] 

instead of

# without `names` parameter
df[0]
df[1]

Explain

Based on read_csv, when names are passed explicitly, then header will be behaving like None instead of 0, so one can skip header=None when names exist.

Answer #3:

Make sure you specify pass header=None and add usecols=[3,6] for the 4th and 7th columns.