'Deleting rows according to specific value in a row
Edition Reviews Ratings BookCategory Price Edition_year
165 Paperback,– Import, 5 Jul 1996 4.5 out of 5 stars 2 customer reviews Sports 270.00 1996
166 Hardcover,– 18 Aug 2009 4.5 out of 5 stars 2 customer reviews Language, Linguistics & Writing 61.00 2009
167 Paperback,– 26 Jul 2018 3.7 out of 5 stars 23 customer reviews Crime, Thriller & Mystery 184.00 2018
168 Paperback,– Import, 22 Mar 2018 4.2 out of 5 stars 50 customer reviews Romance 70.00 2018
169 Paperback,– Abridged, Import 5.0 out of 5 stars 2 customer reviews Action & Adventure 418.00 port
170 Paperback,– 10 Jan 2018 4.7 out of 5 stars 4 customer reviews Sports 395.00 2018
171 Paperback,– Apr 2011 4.0 out of 5 stars 197 customer reviews Language, Linguistics & Writing 179.00 2011
172 Paperback,– 17 Feb 2009 5.0 out of 5 stars 2 customer reviews Comics & Mangas 782.00 2009
173 Paperback,– 22 Aug 2000 3.5 out of 5 stars 4 customer reviews Language, Linguistics & Writing 475.44 2000
174 Paperback,– 5 Jan 2012 4.0 out of 5 stars 30 customer reviews Humour 403.00 2012
Suppose in these dataframe, under Edition_year column, i want to delete rows in which the values of edition year is NOT a numeric value. i.e. there are some values which are strings. I have tried .drop() method but cannot the output required.
This is what i tried:
df = df.drop(df[df['Edition_year'].apply(lambda x: str(x).isalpha())].index, inplace = True)
Solution 1:[1]
You can determinate the Edition_year that are numeric using
numeric_filter = df.Edition_year.astype(str).str.isnumeric()
and then use the filter to select only the desired rows
df = df.loc[numeric_filter]
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Arnau |