根据行中的特定值删除行

Question

    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

假设在这些dataframe中，在Edition_year列下，我希望删除版本年份的值不是数值的行。也就是说，有一些值是字符串。我已经尝试过.drop()方法，但不能满足所需的输出。

这就是我试过的：

df = df.drop(df[df['Edition_year'].apply(lambda x: str(x).isalpha())].index, inplace = True)

Answer 1

您可以使用以下方法确定数值的Edition_year

numeric_filter = df.Edition_year.astype(str).str.isnumeric()

然后使用筛选器只选择所需的行。

df = df.loc[numeric_filter]