How to delete rows from df1 where the column2 value doesn't appear in df2col1

Make sure you don’t have whitespace at the start or end of tha values inside your DataFrame or column names, as the guys pointed out above. i will try to show how to do it in this answer.

# striping whitespace from col names for both DataFrames

df1.rename(columns=lambda x: x.strip(), inplace = True)
df2.rename(columns=lambda x: x.strip(), inplace = True)

# striping whitespace from values in both DataFrames

df1 = df1.apply(lambda x: x.str.strip())
df2 = df2.apply(lambda x: x.str.strip())

# droping rows from df1 where the col2 value doesn't appear in df2 col1

mask = df1["col2"].isin(df2["col1"]) # returns a series of boolean mask(True or False, for the condition we are looking for)

new_df = df1[mask] # Returns what you are asking for :D

Hope this helps.