基于在DataFrame中找到的字符串的Pandas New Column

Question

Trying to match an ID value in one DataFrame to a string column in another DataFrame to create a new ID field.

I have two dataframes, one with an text ID column only:

DF1

ID
elf
orc
panda

And another dataframe with a different ID but a text column that would contain the ID value from the first DataFrame (DF1):

DF2

AltID Text
1     The orc killed the dwarf
2     The elf lives in the woods
3     The panda eats bamboo

That way I can create New ID column in the second Dataframe (DF2) that would look like this if the text is found:

NewID
orc
elf
panda

Should I use a lambda function or an np.where()?

Thanks in advance.

EDIT:

What if it needs to be an exact match? For instance I have this row of text but don't want to match 'orc'

AltID  Text
4      The orchestra played too long

and wanted it to output 'None', N/A or something of that nature for the NewID?

Answer 1

Straightforward using str.extract :

df2['New ID'] = df2.Text.str.extract('({})'.format('|'.join(df1.ID)), expand=False)

df2

   AltID                        Text New ID
0      1    The orc killed the dwarf    orc
1      2  The elf lives in the woods    elf
2      3       The panda eats bamboo  panda

Answer 2

A small trick .

df2.Text.replace(dict(zip(df1.ID,df1.index)),regex=True).map(df1.ID)
Out[1004]: 
0      orc
1      elf
2    panda
Name: Text, dtype: object