<p>另一种方式:</p>
<pre><code>cols=['Region','Rank 2015','Score 2015','Economy 2015','Family 2015','Health 2015','Freedom 2015','Generosity 2015', 'Trust 2015','Rank 2016','Score 2016','Economy 2016','Family 2016','Health 2016','Freedom 2016','Generosity 2016','Trust 2016', 'Rank 2017','Score 2017','Economy 2017','Family 2017','Health 2017','Freedom 2017','Generosity 2017','Trust 2017','Rank 2018','Score 2018','Economy 2018','Family 2018','Health 2018','Freedom 2018','Generosity 2018','Trust 2018','Rank 2019','Score 2019','Economy 2019','Family 2019','Health 2019','Freedom 2019','Generosity 2019','Trust 2019','Score Mean','Economy Mean','Family Mean','Health Mean','Freedom Mean','Generosity Mean','Trust Mean']
# source dataframe
df1 = pd.DataFrame(columns=cols)
df1.loc[0] = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
#target dataframe
df2 = pd.DataFrame(columns=['Year','Rank','Score','Family','Health','Freedom','Generosity','Trust','Economy'])
df2['Year']=['2015','2016','2017','2018','2019','Mean']
df2.set_index('Year', inplace=True)
idx = 0 # source row to copy
for col in df1.columns[1:]:
c,r = col.split(" ")
df2.at[r,c] = df1.at[idx, col]
print (df2)
</code></pre>
<hr/>
<pre><code> Rank Score Family Health Freedom Generosity Trust Economy
Year
2015 1 1 1 1 1 1 1 1
2016 1 1 1 1 1 1 1 1
2017 1 1 1 1 1 1 1 1
2018 1 1 1 1 1 1 1 1
2019 1 1 1 1 1 1 1 1
Mean NaN 1 1 1 1 1 1 1
</code></pre>