Pandas/Python：如何使用函数过滤 Dataframe 或系列？

Question

I have a Dataframe df with among others the columns "Age" and "Name" in my Jupyter Notebook

Usually, when I just want entries fulfilling certian criteria, I filter eg by

df[df["Age"]>20]

meaning "df where df["Age"] happens to be above 20 and therefore it shows only the entries of the df where age is above 20

Now I want to get only the entries where the Name contains "Alex"

df[df["Name"].find("Alex")>-1]         #(".find" returns -1 if Alex is not in in the checked string)

Acutually this does not work seemingly because this function gets applied to the whole series, which is obviously nonsense and therefore gives an error. I would not have expected this behavior because df["Age"]>20 in the first example also worked (meaning it got applied to every single cell of "Age" and not to the series itself). Any ideas how I fix this?

Yours sincerely:)

Answer 1

alex_df = df[df['Name'] == 'Alex']  

If you have multiple names you can use the following.:

name_list = ['Alex', 'Sam', 'Donna']

names_df = df[df['Name'].isin(name_list)] 

Answer 2

Searching for rows where column Name contains Alex as a substring is probably easiest with pandas string accessors:

df[df["Name"].str.contains("Alex")]

More details can be found in the documentation of pandas.