Iterating over two dfs and add values - pandas

Question

I have a dataframe along the lines of the below (df1):
Country Crisis
1 Italy 2008
2 Germany 2008, 2009
3 Mexico
4 US 2007
5 Greece 2010, 2007
I have another dataframe (df2) in panel data format:
Country Year
1 Italy 2007
2 Italy 2008
3 Italy 2009
4 Italy 2010
5 Germany 2007
6 Germany 2008
7 Germany 2009
8 Germany 2010
9 Mexico 2007
10 Mexico 2008
11 Mexico 2009
12 Mexico 2010
13 US 2007
14 US 2008
15 US 2009
16 US 2010
17 Greece 2007
18 Greece 2008
19 Greece 2009
20 Greece 2010
I wish to add a column to df2, "crisis", in which 1 will indicate a crisis, like so:
Country Year crisis
1 Italy 2007 0
2 Italy 2008 1
3 Italy 2009 0
4 Italy 2010 0
5 Germany 2007 0
6 Germany 2008 1
7 Germany 2009 1
8 Germany 2010 0
9 Mexico 2007 0
10 Mexico 2008 0
11 Mexico 2009 0
12 Mexico 2010 0
13 US 2007 1
14 US 2008 0
15 US 2009 0
16 US 2010 0
17 Greece 2007 1
18 Greece 2008 0
19 Greece 2009 0
20 Greece 2010 1
Any ideas?

Answer 1

Although not pretty, this works:
df2['crisis'] = df2.groupby('Country', sort=False, as_index=False).apply(lambda x: x['Year'].isin(df1[df1['Country'] == x['Country'].iloc[0]]['Crisis'].iloc[0])).droplevel(0)
Output:
>>> df2
Country Year crisis
1 Italy 2007 False
2 Italy 2008 True
3 Italy 2009 False
4 Italy 2010 False
5 Germany 2007 False
6 Germany 2008 True
7 Germany 2009 True
8 Germany 2010 False
9 Mexico 2007 False
10 Mexico 2008 False
11 Mexico 2009 False
12 Mexico 2010 False
13 US 2007 True
14 US 2008 False
15 US 2009 False
16 US 2010 False
17 Greece 2007 True
18 Greece 2008 False
19 Greece 2009 False
20 Greece 2010 True
>>> df2.assign(crisis=df2['crisis'].astype(int))
Country Year crisis
1 Italy 2007 0
2 Italy 2008 1
3 Italy 2009 0
4 Italy 2010 0
5 Germany 2007 0
6 Germany 2008 1
7 Germany 2009 1
8 Germany 2010 0
9 Mexico 2007 0
10 Mexico 2008 0
11 Mexico 2009 0
12 Mexico 2010 0
13 US 2007 1
14 US 2008 0
15 US 2009 0
16 US 2010 0
17 Greece 2007 1
18 Greece 2008 0
19 Greece 2009 0
20 Greece 2010 1