擅长:python、mysql、java
<p><strong>设置</strong></p>
<pre><code>df=pd.DataFrame({'Party': {0: 'Democratic', 1: 'Republican', 2: 'Republican'},
'President': {0: 'WoodrowWilson', 1: 'WarrenG.Harding', 2: 'WarrenG.Harding'},
'Value': {0: np.nan, 1: 0.12717200000000001, 2: 0.21738600000000002},
'Year': {0: 1920, 1: 1921, 2: 1922}})
df
Out[1243]:
Party President Value Year
0 Democratic WoodrowWilson NaN 1920
1 Republican WarrenG.Harding 0.127172 1921
2 Republican WarrenG.Harding 0.217386 1922
#you can do this without a loop using groupby.
df_Democrat = df.rename(columns={'Value':'Return'}).groupby('Party')['Party','Year','Return'].get_group('Democratic')
Out[1238]:
Party Year Return
0 Democratic 1920 NaN
df_Republican = df.rename(columns={'Value':'Return'}).groupby('Party')['Party','Year','Return'].get_group('Republican')
Out[1239]:
Party Year Return
1 Republican 1921 0.127172
2 Republican 1922 0.217386
</code></pre>