How can I delete "NaN" fields(rows) in a ".CSV" file with python?

Asked Mar 03 '19 at 05:41

Active Mar 03 '19 at 05:41

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I read a .CSV file with 1000 rows and 10 columns by this code:

dataset = pd.read_csv(r'C:\Users\a.csv')

But it seems there is some NaN elemnts in the read file. So I want to write a code that finds the rows that contain NaN elements and completely delete those rows. For example dataset[100][7]= 'Nan'So it should delete the row 100 completely.

How can I do this?

asked Mar 03 '19 at 05:41

WDR

Use `df = df.dropna()` – jezrael Mar 03 '19 at 05:42
@jezrael: If one element in a row is `NaN` will this command remove the whole row or just the `NaN` element? – WDR Mar 03 '19 at 05:44
1

It remove always row, not possible remove NaN without row. – jezrael Mar 03 '19 at 05:44

How can I delete "NaN" fields(rows) in a ".CSV" file with python?

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