Pandas reading empty rows into dataframe from csv

Question

I am reading a csv into a dataframe using:

import pandas as pd
df = pd.read_csv('file.csv')

My csv has 800 rows of data, but my dataframe is reading in 805 rows. The last 5 rows are completely blank. Is there any way to remove these 5 empty rows?

you can use built-in function dropna() for NaN data

mtkilic
– mtkilic

2017-07-17 19:14:39 +00:00
Commented Jul 17, 2017 at 19:14 — mtkilic
– mtkilic, Commented Jul 17, 2017 at 19:14
you can also try df=pd.read_csv('file.csv', skipfooter=5)

juan
– juan

2017-07-18 14:02:41 +00:00
Commented Jul 18, 2017 at 14:02 — juan
– juan, Commented Jul 18, 2017 at 14:02

akuiper · Accepted Answer · 2017-07-17 19:15:35Z

2

You can use slice with iloc to remove last 5 rows, if you don't bother reading the data again and just want to work with the current copy:

df = df.iloc[:-5]

Or use head:

df.head(-5)

answered Jul 17, 2017 at 19:15

akuiper

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William Miller · Accepted Answer · 2019-12-01 23:16:16Z

1

You have a few options when using the read_csv() from pandas which is documented here.

I think the easiest one-time argument you can pass into the function would be along the lines of pd.read_csv('file.csv', skiprows = 801:805)

For more reusable code you can try some of the others on that site like skip_blank_lines which is defaulted to True anyways, so make sure those rows are actually blank in your file.

edited Dec 1, 2019 at 23:16

William Miller

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answered Jul 17, 2017 at 19:18

Alex Braksator

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