How do I skip lines and parse dates as index in python

Question

I have a csv file that contains 90000 lines with a date format index. I don't need to read the first 9 lines because that's info that doesn't concern me. I've tried like this:

df_dados = pd.read_csv('dados.csv', skiplines=9, index_col=0, parse_dates=['timestamp'])

Unfortunally it doesn't work, and the only way I've surpassed this is by modifying the file which I wouldn't like to do. Is there a way to skip lines and set the time index?

Look if this is useful stackoverflow.com/questions/14674275/… Give me a feedback ;) — ElMaestroDeToMare
– ElMaestroDeToMare, Commented May 19, 2021 at 15:00
I think the correct parameter name is skiprows, not skiplines. — John Gordon
– John Gordon, Commented May 19, 2021 at 15:01

Jacob Lee · Accepted Answer · 2021-05-19 15:00:32Z

0

The skiprows argument of pandas.read_csv() can be either list-like, an integer, or a callable.

List-like: Contains the line numbers to skip
Integer: Contains the line number to skip
Callable: Returns True or False depending on whether the row should be skipped or not.

Since you want to skip the first 9 lines, try passing skiprows=range(9).

df_dados = pd.read_csv('dados.csv', skiprows=range(9), index_col=0, parse_dates=['timestamp'])

Note: The line numbers to skip are 0-indexed (first line is index 0, second is index 1, etc.).

answered May 19, 2021 at 15:00

Jacob Lee

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1 Comment

AmaFor Over a year ago

It worked worderfully. Thank you very much

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