基于另一个 dataframe 列在 dataframe 中添加新列

Question

Let's assume we have the following 2 dataframes:

df1(36000, 20) and  df2(80,6)
They have 3 columns in common(let's say Name, Last Name, Date)

df1 includes the data of df2 (minus the data in the 3 different columns) and of course some extra information.
df2 has a column that I am interested (let' s name it Rent)

What I want is to create an extra column in df1 that for the values that of df2 to have the value "Overdue" and for the values that are not there have "Due" while keeping the rest of columns in df1. I tried the following

  merged = df1.merge(df2, how='left', on=list(df1.columns),
                                   indicator=True)
    df1['Rent'] = np.where(merged['_merge'] == 'both', 'Overdue', 'Due')

However I get an error due to the fact that not all columns of df1 exist in df2. Any ideas?

Also I tried the following

    df1['Rent'].apply(lambda x: 'Overdue' if df1['Name'].isin(df2['Name']) else 'Due')

but I m getting the following error

AttributeError: 'function' object has no attribute 'df2'

Answer 1

Try this:

df1['Rent'] = lambda x: 'Overdue' if df1['Name'].isin(df2['Name']) else 'Due'

The main point is not to use.apply()